Topic Editors

Faculty of Information Technology and Electrical Engineering, University of Oulu, 90570 Oulu, Finland
School of Computer Science and Technology, Hangzhou Dianzi University Hangzhou, Hangzhou 310008, China
Dr. Mohammed Aquil Mirza
Department of Building and Real Estate, The Hong Kong Polytechnic University (PolyU), Hong Kong, China
Department of Economics, Division of Mathematics and Informatics, National and Kapodistrian University of Athens, Zografou, Greece
School of Mathematical Sciences, Tongji University, Shanghai, China
Faculty of Sciences and Mathematics, University of Niš, Višegradska 33, 18106 Niš, Serbia

Intelligent Systems and Robotics

Abstract submission deadline
closed (30 April 2023)
Manuscript submission deadline
closed (30 June 2023)
Viewed by
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Topic Information

Dear Colleagues,

This topic mainly focuses on the control and analysis of systems and robotics, such as complex systems, nonlinear dynamics, neural networks, data management, novel computational algorithms, mobile robots and articulated robots. Research on generalized system theory, distributed intelligent systems, bioengineering, robotics and systems, computational social behaviors, medical robotics, mechatronics, unmanned systems, multi-robot teams and networked swarms, machine intelligence, learning, system autonomy and autonomous systems, design for autonomy, cyber physical systems, and other related areas in which cutting-edge technologies have been developed and applied to model, design, build, and test complex engineering and autonomous systems, robot modeling, motion control methods, and computer vision algorithms are welcome to contribute to this topic.

Prof. Dr. Shuai Li
Prof. Dr. Dechao Chen
Dr. Mohammed Aquil Mirza
Dr. Vasilios N. Katsikis
Prof. Dr. Dunhui Xiao
Prof. Dr. Predrag S. Stanimirović
Topic Editors

Participating Journals

Journal Name Impact Factor CiteScore Launched Year First Decision (median) APC
Energies
energies
3.0 6.2 2008 16.1 Days CHF 2600
Machines
machines
2.1 3.0 2013 15.6 Days CHF 2400
Robotics
robotics
2.9 6.7 2012 17.3 Days CHF 1800
Sensors
sensors
3.4 7.3 2001 17 Days CHF 2600
Systems
systems
2.3 2.8 2013 16.8 Days CHF 2400
Algorithms
algorithms
1.8 4.1 2008 15 Days CHF 1600
Mathematics
mathematics
2.3 4.0 2013 16.9 Days CHF 2600
Automation
automation
- 2.9 2020 26.3 Days CHF 1000

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Published Papers (49 papers)

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19 pages, 10934 KiB  
Article
Staircase Recognition and Localization Using Convolutional Neural Network (CNN) for Cleaning Robot Application
by Muhammad Ilyas, Anirudh Krishna Lakshmanan, Anh Vu Le and Mohan Rajesh Elara
Mathematics 2023, 11(18), 3964; https://doi.org/10.3390/math11183964 - 18 Sep 2023
Viewed by 1294
Abstract
Floor-cleaning robots are primarily designed to clean on a single floor, while multi-floor environments are usually not considered target applications. However, it is more efficient to have an autonomous floor-cleaning robot that can climb stairs and reach the next floors in a multi-floor [...] Read more.
Floor-cleaning robots are primarily designed to clean on a single floor, while multi-floor environments are usually not considered target applications. However, it is more efficient to have an autonomous floor-cleaning robot that can climb stairs and reach the next floors in a multi-floor building. To operate in such environments, the ability of a mobile robot to autonomously traverse staircases is very important. For this operation, staircase detection and localization are essential components for planning the traversal route on staircases. This article describes a deep learning approach using a convolutional neural network (CNN)-based robot operation system (ROS) framework for staircase detection, localization, and maneuvering of the robot to the detected stair. We present a real-time object detection framework to detect staircases in incoming images. We also localize these staircases using a contour detection algorithm to detect the target point: a point close to the center of the first step, and an angle of approach to the target point with respect to the current location of the robot. Experiments are performed with data from images captured on different types of staircases at different viewpoints/angles. The experimental results show that the presented approach can achieve an accuracy of 95% and a recall of 86.81%. A total runtime of 155 ms is taken to identify the presence of a staircase and the detection of the first step in the working environment, as well as being able to locate the target point with an accuracy of ±2 cm, ±1 degree. Full article
(This article belongs to the Topic Intelligent Systems and Robotics)
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15 pages, 2180 KiB  
Article
Model-Free Adaptive Positioning Control of the Bidirectional Stick–Slip Piezoelectric Actuator with Coupled Asymmetric Flexure-Hinge Mechanisms
by Zhenguo Zhang, Yikun Dong, Shuai Yu, Xiaohui Lu and Keping Liu
Sensors 2023, 23(18), 7795; https://doi.org/10.3390/s23187795 - 11 Sep 2023
Cited by 2 | Viewed by 970
Abstract
A model-free adaptive positioning control strategy for piezoelectric stick–slip actuators (PSSAs) with uncertain disturbance is proposed. The designed controller consists of a data-driven self-learning feedforward controller and a model-free adaptive feedback controller with a radial basis function neural network (RBFNN)-based observer. Unlike the [...] Read more.
A model-free adaptive positioning control strategy for piezoelectric stick–slip actuators (PSSAs) with uncertain disturbance is proposed. The designed controller consists of a data-driven self-learning feedforward controller and a model-free adaptive feedback controller with a radial basis function neural network (RBFNN)-based observer. Unlike the traditional model-based control methods, the model-free adaptive control (MFAC) strategy avoids the complicated modeling process. First, the nonlinear system of the PSSA is dynamically linearized into a data model. Then, the model-free adaptive feedback controller based on a data model is designed to avoid the complicated modeling process and enhance the robustness of the control system. Simultaneously, the data-driven self-learning feedforward controller is improved to realize the high-precision control performance. Additionally, the convergence of the tracking error and the boundedness of the control output signal are proved. Finally, the experimentally obtained results illustrate the advantages and effectiveness of the developed control methodology on the bidirectional stick–slip piezoelectric actuator with coupled asymmetric flexure-hinge mechanisms. The positioning error through the proposed controller reaches 30 nm under the low-frequency condition and 200 nm under the high-frequency condition when the target position is set to 100 μm. In addition, the target position can be accurately tracked in less than 0.5 s in the presence of a 100 Hz frequency. Full article
(This article belongs to the Topic Intelligent Systems and Robotics)
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0 pages, 6995 KiB  
Article
Attitude Control of UAVs with Search Optimization and Disturbance Rejection Strategies
by Wensheng Li, Fanke Yang, Liqiang Zhong, Hao Wu, Xiangyuan Jiang and Andrei V. Chukalin
Mathematics 2023, 11(17), 3794; https://doi.org/10.3390/math11173794 - 4 Sep 2023
Cited by 1 | Viewed by 1235 | Correction
Abstract
This study aims to achieve rapid and stable control of quadrotor unmanned aerial vehicles’ (UAVs) attitude by using an Active Disturbance Rejection Control (ADRC) controller. Addressing the challenge of numerous and complex ADRC parameters, optimization algorithms are employed for parameter tuning. This paper [...] Read more.
This study aims to achieve rapid and stable control of quadrotor unmanned aerial vehicles’ (UAVs) attitude by using an Active Disturbance Rejection Control (ADRC) controller. Addressing the challenge of numerous and complex ADRC parameters, optimization algorithms are employed for parameter tuning. This paper draws on the group mechanism of the Ant Colony Optimization (ACO) algorithm and innovatively introduces population search into the Beetle Antennae Search (BAS) algorithm. The refined algorithm is then applied to tune the ADRC parameters, reducing complexity and human intervention while enhancing intelligence and efficiency. The advanced optimization algorithm exhibits an exceptional global optimization capacity, convergence speed, and stability. Ultimately, flight simulation and experimental results suggest that the optimized ADRC controller demonstrates superior control and antidisturbance capabilities. Full article
(This article belongs to the Topic Intelligent Systems and Robotics)
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13 pages, 2679 KiB  
Article
Design of an Intelligent Shop Scheduling System Based on Internet of Things
by Maoyun Zhang, Yuheng Jiang, Chuan Wan, Chen Tang, Boyan Chen and Huizhuang Xi
Energies 2023, 16(17), 6310; https://doi.org/10.3390/en16176310 - 30 Aug 2023
Viewed by 779
Abstract
In order to optimize the functionality of automated guidance vehicles (AGVs) in logistics workshops, a wireless charging and task-based logistics intelligent dispatch system was developed based on the Internet of Things. This system aimed to improve freight efficiency in the workshop’s logistics system. [...] Read more.
In order to optimize the functionality of automated guidance vehicles (AGVs) in logistics workshops, a wireless charging and task-based logistics intelligent dispatch system was developed based on the Internet of Things. This system aimed to improve freight efficiency in the workshop’s logistics system. The scheduling system successfully addressed the round-trip scheduling issue between AGVs and multiple tasks through two degrees of improvement: the application of AGVs and task path planning. To handle conflict coordination and AGV cluster path planning, a shortest path planning algorithm based on the A* search algorithm was proposed, and the traffic control law was enhanced. The initial population of genetic algorithms, which used greedy algorithms to solve problems, was found to be too large in terms of task distribution. To address this, the introduction of a few random individuals ensured population diversity and helped avoid local optima. Numerical experiments demonstrated a significantly accelerated convergence rate towards the optimal solution. Full article
(This article belongs to the Topic Intelligent Systems and Robotics)
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16 pages, 4751 KiB  
Article
Hand-Guiding Gesture-Based Telemanipulation with the Gesture Mode Classification and State Estimation Using Wearable IMU Sensors
by Haegyeom Choi, Haneul Jeon, Donghyeon Noh, Taeho Kim and Donghun Lee
Mathematics 2023, 11(16), 3514; https://doi.org/10.3390/math11163514 - 14 Aug 2023
Cited by 3 | Viewed by 1058
Abstract
This study proposes a telemanipulation framework with two wearable IMU sensors without human skeletal kinematics. First, the states (intensity and direction) of spatial hand-guiding gestures are separately estimated through the proposed state estimator, and the states are also combined with the gesture’s mode [...] Read more.
This study proposes a telemanipulation framework with two wearable IMU sensors without human skeletal kinematics. First, the states (intensity and direction) of spatial hand-guiding gestures are separately estimated through the proposed state estimator, and the states are also combined with the gesture’s mode (linear, angular, and via) obtained with the bi-directional LSTM-based mode classifier. The spatial pose of the 6-DOF manipulator’s end-effector (EEF) can be controlled by combining the spatial linear and angular motions based on integrating the gesture’s mode and state. To validate the significance of the proposed method, the teleoperation of the EEF to the designated target poses was conducted in the motion-capture space. As a result, it was confirmed that the mode could be classified with 84.5% accuracy in real time, even during the operator’s dynamic movement; the direction could be estimated with an error of less than 1 degree; and the intensity could be successfully estimated with the gesture speed estimator and finely tuned with the scaling factor. Finally, it was confirmed that a subject could place the EEF within the average range of 83 mm and 2.56 degrees in the target pose with only less than ten consecutive hand-guiding gestures and visual inspection in the first trial. Full article
(This article belongs to the Topic Intelligent Systems and Robotics)
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24 pages, 3619 KiB  
Article
Depth-Dependent Control in Vision-Sensor Space for Reconfigurable Parallel Manipulators
by Arturo Franco-López, Mauro Maya, Alejandro González, Antonio Cardenas and Davide Piovesan
Sensors 2023, 23(16), 7039; https://doi.org/10.3390/s23167039 - 9 Aug 2023
Viewed by 1399
Abstract
In this paper, a control approach for reconfigurable parallel robots is designed. Based on it, controls in the vision-sensor, 3D and joint spaces are designed and implemented in target tracking tasks in a novel reconfigurable delta-type parallel robot. No a priori information about [...] Read more.
In this paper, a control approach for reconfigurable parallel robots is designed. Based on it, controls in the vision-sensor, 3D and joint spaces are designed and implemented in target tracking tasks in a novel reconfigurable delta-type parallel robot. No a priori information about the target trajectory is required. Robot reconfiguration can be used to overcome some of the limitations of parallel robots like small relative workspace or multiple singularities, at the cost of increasing the complexity of the manipulator, making its control design even more challenging. No general control methodology exists for reconfigurable parallel robots. Tracking objects with unknown trajectories is a challenging task required in many applications. Sensor-based robot control has been actively used for this type of task. However, it cannot be straightforwardly extended to reconfigurable parallel manipulators. The developed vision-sensor space control is inspired by, and can be seen as an extension of, the Velocity Linear Camera Model–Camera Space Manipulation (VLCM-CSM) methodology. Several experiments were carried out on a reconfigurable delta-type parallel robot. An average positioning error of 0.6 mm was obtained for static objectives. Tracking errors of 2.5 mm, 3.9 mm and 11.5 mm were obtained for targets moving along a linear trajectory at speeds of 6.5, 9.3 and 12.7 cm/s, respectively. The control cycle time was 16 ms. These results validate the proposed approach and improve upon previous works for non-reconfigurable robots. Full article
(This article belongs to the Topic Intelligent Systems and Robotics)
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25 pages, 5019 KiB  
Article
Task-Oriented Systematic Design of a Heavy-Duty Electrically Actuated Quadruped Robot with High Performance
by Junjun Liu, Zeyu Wang, Letian Qian, Rong Luo and Xin Luo
Sensors 2023, 23(15), 6696; https://doi.org/10.3390/s23156696 - 26 Jul 2023
Viewed by 1376
Abstract
Recent technological progress is opening up practical applications for quadruped robots. In this context, comprehensive performance demands, including speed, payload, robustness, terrain adaptability, endurance, and techno-economics, are increasing. However, design conflicts inevitably exist among these performance indicators, highlighting design challenges, especially for a [...] Read more.
Recent technological progress is opening up practical applications for quadruped robots. In this context, comprehensive performance demands, including speed, payload, robustness, terrain adaptability, endurance, and techno-economics, are increasing. However, design conflicts inevitably exist among these performance indicators, highlighting design challenges, especially for a heavy-duty, electrically actuated quadruped robots, which are strongly constrained by motor torque density and battery energy density. Starting from task-specific holistic system thinking, in this paper, we present a novel task-oriented approach to the design of such kind of robots, incorporating hierarchical optimization and a control-in-the-loop design, while following a structured design path that effectively exploits the strengths of both heuristic and computational designs. Guided by these philosophies, we utilize heuristic design to obtain the approximate initial form of the prototype and propose a key task-oriented actuator joint configuration, utilizing commercially available components. Subsequently, we build a step-wise analytical models considering trajectory optimization and motor heat constraints for optimization of leg length and joint match parameters to achieve a compact performance requirement envelope and minimize redundancy in the construction of task-specific components. Furthermore, we construct a holistic simulation platform with a module control algorithm for typical scenarios to evaluate subsystem results and adjust design parameters iteratively, balancing conflicts and eventually achieving a reliable design specification for detailed subsystem design. Based on these strategies, we develop a heavy-duty electric prototype achieving a maximum speed of 2 m/s in trotting gait with a load weighting over 160 kg and enduring a period of 2 h. The experiment upon the prototype verifies the efficiency of the proposed approach. Full article
(This article belongs to the Topic Intelligent Systems and Robotics)
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20 pages, 5543 KiB  
Article
Failure Mode and Effect Analysis with a Fuzzy Logic Approach
by José Jovani Cardiel-Ortega and Roberto Baeza-Serrato
Systems 2023, 11(7), 348; https://doi.org/10.3390/systems11070348 - 7 Jul 2023
Cited by 7 | Viewed by 1514
Abstract
Failure mode and effect analysis (FMEA) is one of the most used techniques in risk management due to its potential to solve multidisciplinary engineering problems. The role of experts is fundamental when developing the FMEA; they identify the failure modes by expressing their [...] Read more.
Failure mode and effect analysis (FMEA) is one of the most used techniques in risk management due to its potential to solve multidisciplinary engineering problems. The role of experts is fundamental when developing the FMEA; they identify the failure modes by expressing their opinion based on their experience. A relevant aspect is a way in which the experts evaluate to obtain the indicator of the risk priority number (RPN), which is based on qualitative analysis and a table of criteria where they subjectively and intuitively determine the factor level (severity, occurrence, and detection) for each of the failures. With this, imprecision is present due to the interpretation that each one has regarding the failures. Therefore, this research proposes a fuzzy logic evaluation system with a solid mathematical basis that integrates these conditions of imprecision and uncertainty, thus offering a robust system capable of emulating the evaluation form of experts to support and improve decision making. One of the main contributions of this research is in the defuzzification stage, adjusting the centroid method and treating each set individually. With this, the RPN values approximate to the conventional technique were obtained. Simulations were carried out to test and determine the system’s best structure. The system was validated in a textile company in southern Guanajuato. The results demonstrate that the system reliably represents how experts perform risk assessment. Full article
(This article belongs to the Topic Intelligent Systems and Robotics)
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16 pages, 2400 KiB  
Article
Risk-Sensitive Policy with Distributional Reinforcement Learning
by Thibaut Théate and Damien Ernst
Algorithms 2023, 16(7), 325; https://doi.org/10.3390/a16070325 - 30 Jun 2023
Cited by 2 | Viewed by 1605
Abstract
Classical reinforcement learning (RL) techniques are generally concerned with the design of decision-making policies driven by the maximisation of the expected outcome. Nevertheless, this approach does not take into consideration the potential risk associated with the actions taken, which may be critical in [...] Read more.
Classical reinforcement learning (RL) techniques are generally concerned with the design of decision-making policies driven by the maximisation of the expected outcome. Nevertheless, this approach does not take into consideration the potential risk associated with the actions taken, which may be critical in certain applications. To address that issue, the present research work introduces a novel methodology based on distributional RL to derive sequential decision-making policies that are sensitive to the risk, the latter being modelled by the tail of the return probability distribution. The core idea is to replace the Q function generally standing at the core of learning schemes in RL by another function, taking into account both the expected return and the risk. Named the risk-based utility function U, it can be extracted from the random return distribution Z naturally learnt by any distributional RL algorithm. This enables the spanning of the complete potential trade-off between risk minimisation and expected return maximisation, in contrast to fully risk-averse methodologies. Fundamentally, this research yields a truly practical and accessible solution for learning risk-sensitive policies with minimal modification to the distributional RL algorithm, with an emphasis on the interpretability of the resulting decision-making process. Full article
(This article belongs to the Topic Intelligent Systems and Robotics)
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42 pages, 21970 KiB  
Article
UPAFuzzySystems: A Python Library for Control and Simulation with Fuzzy Inference Systems
by Martín Montes Rivera, Ernesto Olvera-Gonzalez and Nivia Escalante-Garcia
Machines 2023, 11(5), 572; https://doi.org/10.3390/machines11050572 - 22 May 2023
Cited by 2 | Viewed by 3622
Abstract
The main goal of control theory is input tracking or system stabilization. Different feedback-computed controlled systems exist in this area, from deterministic to soft methods. Some examples of deterministic methods are Proportional (P), Proportional Integral (PI), Proportional Derivative (PD), Proportional Integral Derivative (PID), [...] Read more.
The main goal of control theory is input tracking or system stabilization. Different feedback-computed controlled systems exist in this area, from deterministic to soft methods. Some examples of deterministic methods are Proportional (P), Proportional Integral (PI), Proportional Derivative (PD), Proportional Integral Derivative (PID), Linear Quadratic (LQ), Linear Quadratic Gaussian (LQG), State Feedback (SF), Adaptative Regulators, and others. Alternatively, Fuzzy Inference Systems (FISs) are soft-computing methods that allow using the human expertise in logic in IF–THEN rules. The fuzzy controllers map the experience of an expert in controlling the plant. Moreover, the literature shows that optimization algorithms allow the adaptation of FISs to control different processes as a black-box problem. Python is the most used programming language, which has seen the most significant growth in recent years. Using open-source libraries in Python offers numerous advantages in software development, including saving time and resources. In this paper, we describe our proposed UPAFuzzySystems library, developed as an FISs library for Python, which allows the design and implementation of fuzzy controllers with transfer-function and state-space simulations. Additionally, we show the use of the library for controlling the position of a DC motor with Mamdani, FLS, Takagi–Sugeno, fuzzy P, fuzzy PD, and fuzzy PD-I controllers. Full article
(This article belongs to the Topic Intelligent Systems and Robotics)
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18 pages, 6238 KiB  
Article
A Minimalist Self-Localization Approach for Swarm Robots Based on Active Beacon in Indoor Environments
by Mengyuan Duan, Xiaokang Lei, Zhongxing Duan and Zhicheng Zheng
Sensors 2023, 23(10), 4926; https://doi.org/10.3390/s23104926 - 20 May 2023
Cited by 1 | Viewed by 1861
Abstract
When performing indoor tasks, miniature swarm robots are suffered from their small size, poor on-board computing power, and electromagnetic shielding of buildings, which means that some traditional localization methods, such as global positioning system (GPS), simultaneous localization and mapping (SLAM), and ultra-wideband (UWB), [...] Read more.
When performing indoor tasks, miniature swarm robots are suffered from their small size, poor on-board computing power, and electromagnetic shielding of buildings, which means that some traditional localization methods, such as global positioning system (GPS), simultaneous localization and mapping (SLAM), and ultra-wideband (UWB), cannot be employed. In this paper, a minimalist indoor self-localization approach for swarm robots is proposed based on active optical beacons. A robotic navigator is introduced into a swarm of robots to provide locally localization services by actively projecting a customized optical beacon on the indoor ceiling, which contains the origin and the reference direction of localization coordinates. The swarm robots observe the optical beacon on the ceiling via a bottom-up-view monocular camera, and extract the beacon information on-board to localize their positions and headings. The uniqueness of this strategy is that it uses the flat, smooth, and well-reflective ceiling in the indoor environment as a ubiquitous plane for displaying the optical beacon; meanwhile, the bottom-up view of swarm robots is not easily blocked. Real robotic experiments are conducted to validate and analyze the localization performance of the proposed minimalist self-localization approach. The results show that our approach is feasible and effective, and can meet the needs of swarm robots to coordinate their motion. Specifically, for the stationary robots, the average position error and heading error are 2.41 cm and 1.44°; when the robots are moving, the average position error and heading error are less than 2.40 cm and 2.66°. Full article
(This article belongs to the Topic Intelligent Systems and Robotics)
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17 pages, 4484 KiB  
Article
Hybrid Vibration Control Algorithm of a Flexible Manipulator System
by Van Binh Nguyen and Xuan Cuong Bui
Robotics 2023, 12(3), 73; https://doi.org/10.3390/robotics12030073 - 15 May 2023
Cited by 3 | Viewed by 1850
Abstract
Flexible manipulator systems in specific applications such as space exploration, nuclear waste treatment, medical applications, etc., often have characteristics superior to conventional rigid manipulator systems. However, their elasticity and complex dynamics lead to difficulties encountered in control processes. Research on improving the structure [...] Read more.
Flexible manipulator systems in specific applications such as space exploration, nuclear waste treatment, medical applications, etc., often have characteristics superior to conventional rigid manipulator systems. However, their elasticity and complex dynamics lead to difficulties encountered in control processes. Research on improving the structure of the control model plays a very important role in reducing the above limitations and achieving great benefits for the flexible manipulator system. In this study, a general method for modelling a flexible robotic manipulator is introduced. Furthermore, two control models for flexible manipulators are proposed. The first model uses two proportional–integral–derivative (PID) controllers, where the first one is used for position control, and the other is applied for vibration reduction. The second model is an enhanced development of the first with the addition of a fuzzy logic controller to optimise oscillation suppression. Selected experimental results are presented and compared to evaluate the performance of the proposed control mechanisms. Full article
(This article belongs to the Topic Intelligent Systems and Robotics)
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28 pages, 8194 KiB  
Article
Designing Behaviors of Robots Based on the Artificial Emotion Expression Method in Human–Robot Interactions
by Liming Li and Zeang Zhao
Machines 2023, 11(5), 533; https://doi.org/10.3390/machines11050533 - 6 May 2023
Cited by 1 | Viewed by 1942
Abstract
How to express emotions through motion behaviors of robots (mainly for robotic arms) to achieve human–robot emotion interactions is the focus of this paper. An artificial emotion expression method that accords with human emotion that can deal with external stimuli and has the [...] Read more.
How to express emotions through motion behaviors of robots (mainly for robotic arms) to achieve human–robot emotion interactions is the focus of this paper. An artificial emotion expression method that accords with human emotion that can deal with external stimuli and has the capability of emotion decision-making was proposed based on the motion behaviors of robot. Firstly, a three-dimensional emotion space was established based on the motion indexes (deviation coefficient, acceleration, and interval time). Then, an artificial emotion model, which was divided into three parts (the detection and processing of external events, the generation and modification of emotion response vectors, and the discretization of emotions) was established in the three-dimensional emotion space. Then emotion patterns (love, excited, happy, anxiety, hate) and emotion intensity were calculated based on the artificial emotion model in human–robot interaction experiments. Finally, the influence of motion behaviors of humanoid robot NAO on the emotion expression of experimenters was studied through human–robot emotion interaction experiments based on the emotion patterns and emotion intensity. The positive emotion patterns (love, excited, happy) and negative emotion patterns (anxiety, hate) of the experimenters were evaluated. The experimental results showed that the personalized emotion responses could be generated autonomously for external stimuli, and the change process of human emotions could be simulated effectively according to the established artificial emotion model. Furthermore, the experimenters could recognize the emotion patterns expressed by the robot according to the motion behaviors of the robot, and whether experimenters were familiar with robots did not influence the recognition of different emotion patterns. Full article
(This article belongs to the Topic Intelligent Systems and Robotics)
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22 pages, 3375 KiB  
Article
An Incremental Inverse Reinforcement Learning Approach for Motion Planning with Separated Path and Velocity Preferences
by Armin Avaei, Linda van der Spaa, Luka Peternel and Jens Kober
Robotics 2023, 12(2), 61; https://doi.org/10.3390/robotics12020061 - 20 Apr 2023
Cited by 4 | Viewed by 2167
Abstract
Humans often demonstrate diverse behaviors due to their personal preferences, for instance, related to their individual execution style or personal margin for safety. In this paper, we consider the problem of integrating both path and velocity preferences into trajectory planning for robotic manipulators. [...] Read more.
Humans often demonstrate diverse behaviors due to their personal preferences, for instance, related to their individual execution style or personal margin for safety. In this paper, we consider the problem of integrating both path and velocity preferences into trajectory planning for robotic manipulators. We first learn reward functions that represent the user path and velocity preferences from kinesthetic demonstration. We then optimize the trajectory in two steps, first the path and then the velocity, to produce trajectories that adhere to both task requirements and user preferences. We design a set of parameterized features that capture the fundamental preferences in a pick-and-place type of object transportation task, both in the shape and timing of the motion. We demonstrate that our method is capable of generalizing such preferences to new scenarios. We implement our algorithm on a Franka Emika 7-DoF robot arm and validate the functionality and flexibility of our approach in a user study. The results show that non-expert users are able to teach the robot their preferences with just a few iterations of feedback. Full article
(This article belongs to the Topic Intelligent Systems and Robotics)
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15 pages, 2964 KiB  
Article
SLP-Improved DDPG Path-Planning Algorithm for Mobile Robot in Large-Scale Dynamic Environment
by Yinliang Chen and Liang Liang
Sensors 2023, 23(7), 3521; https://doi.org/10.3390/s23073521 - 28 Mar 2023
Cited by 5 | Viewed by 2546
Abstract
Navigating robots through large-scale environments while avoiding dynamic obstacles is a crucial challenge in robotics. This study proposes an improved deep deterministic policy gradient (DDPG) path planning algorithm incorporating sequential linear path planning (SLP) to address this challenge. This research aims to enhance [...] Read more.
Navigating robots through large-scale environments while avoiding dynamic obstacles is a crucial challenge in robotics. This study proposes an improved deep deterministic policy gradient (DDPG) path planning algorithm incorporating sequential linear path planning (SLP) to address this challenge. This research aims to enhance the stability and efficiency of traditional DDPG algorithms by utilizing the strengths of SLP and achieving a better balance between stability and real-time performance. Our algorithm generates a series of sub-goals using SLP, based on a quick calculation of the robot’s driving path, and then uses DDPG to follow these sub-goals for path planning. The experimental results demonstrate that the proposed SLP-enhanced DDPG path planning algorithm outperforms traditional DDPG algorithms by effectively navigating the robot through large-scale dynamic environments while avoiding obstacles. Specifically, the proposed algorithm improves the success rate by 12.33% compared to the traditional DDPG algorithm and 29.67% compared to the A*+DDPG algorithm in navigating the robot to the goal while avoiding obstacles. Full article
(This article belongs to the Topic Intelligent Systems and Robotics)
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8 pages, 2039 KiB  
Communication
A New Self-Reconfiguration Wave-like Crawling Robot: Design, Analysis, and Experiments
by Haosheng Sun, Qingxiang Wu, Xuebing Wang, Tong Yang and Ning Sun
Machines 2023, 11(3), 398; https://doi.org/10.3390/machines11030398 - 19 Mar 2023
Cited by 2 | Viewed by 1947
Abstract
Traditional mobile robots with fixed structures lack the ability to cope with complex terrains and tasks. Reconfigurable modular mobile robots have received considerable attention as they can automatically reassemble according to the changing environment or task. In this paper, a new self-reconfiguration wave-like [...] Read more.
Traditional mobile robots with fixed structures lack the ability to cope with complex terrains and tasks. Reconfigurable modular mobile robots have received considerable attention as they can automatically reassemble according to the changing environment or task. In this paper, a new self-reconfiguration wave-like crawling (SWC) robot is presented to improve the mobile robots’ locomotion capacity. First, the mechanical design of the wave-like crawling mechanism is detailed. Then, the series and parallel connections are introduced to achieve self-reconfiguration. In addition, the kinematic model of the SWC robot is established. Finally, experiments were performed to verify the robotic system with wireless data transmission. Full article
(This article belongs to the Topic Intelligent Systems and Robotics)
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20 pages, 7213 KiB  
Article
Estimation of Knee Assistive Moment in a Gait Cycle Using Knee Angle and Knee Angular Velocity through Machine Learning and Artificial Stiffness Control Strategy (MLASCS)
by Khemwutta Pornpipatsakul and Nopdanai Ajavakom
Robotics 2023, 12(2), 44; https://doi.org/10.3390/robotics12020044 - 17 Mar 2023
Cited by 5 | Viewed by 2868
Abstract
Nowadays, many people around the world cannot walk perfectly because of their knee problems. A knee-assistive device is one option to support walking for those with low or not enough knee muscle forces. Many research studies have created knee devices with control systems [...] Read more.
Nowadays, many people around the world cannot walk perfectly because of their knee problems. A knee-assistive device is one option to support walking for those with low or not enough knee muscle forces. Many research studies have created knee devices with control systems implementing different techniques and sensors. This study proposes an alternative version of the knee device control system without using too many actuators and sensors. It applies the machine learning and artificial stiffness control strategy (MLASCS) that uses one actuator combined with an encoder for estimating the amount of assistive support in a walking gait from the recorded gait data. The study recorded several gait data and analyzed knee moments, and then trained a k-nearest neighbor model using the knee angle and the angular velocity to classify a state in a gait cycle. This control strategy also implements instantaneous artificial stiffness (IAS), a control system that requires only knee angle in each state to determine the amount of supporting moment. After validating the model via simulation, the accuracy of the machine learning model is around 99.9% with the speed of 165 observers/s, and the walking effort is reduced by up to 60% in a single gait cycle. Full article
(This article belongs to the Topic Intelligent Systems and Robotics)
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15 pages, 5634 KiB  
Article
Energy Efficiency of a Wheeled Bio-Inspired Hexapod Walking Robot in Sloping Terrain
by Marek Žák, Jaroslav Rozman and František V. Zbořil
Robotics 2023, 12(2), 42; https://doi.org/10.3390/robotics12020042 - 15 Mar 2023
Cited by 1 | Viewed by 2305
Abstract
Multi-legged robots, such as hexapods, have great potential to navigate challenging terrain. However, their design and control are usually much more complex and energy-demanding compared to wheeled robots. This paper presents a wheeled six-legged robot with five degrees of freedom, that is able [...] Read more.
Multi-legged robots, such as hexapods, have great potential to navigate challenging terrain. However, their design and control are usually much more complex and energy-demanding compared to wheeled robots. This paper presents a wheeled six-legged robot with five degrees of freedom, that is able to move on a flat surface using wheels and switch to gait in rugged terrain, which reduces energy consumption. The novel joint configuration mimics the structure of insect limbs and allows our robot to overcome difficult terrain. The wheels reduce energy consumption when moving on flat terrain and the trochanter joint reduces energy consumption when moving on slopes, extending the operating time and range of the robot. The results of experiments on sloping terrain are presented. It was confirmed that the use of the trochanter joint can lead to a reduction in energy consumption when moving in sloping terrain. Full article
(This article belongs to the Topic Intelligent Systems and Robotics)
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18 pages, 12083 KiB  
Article
Exact and Heuristic Multi-Robot Dubins Coverage Path Planning for Known Environments
by Lin Li, Dianxi Shi, Songchang Jin, Shaowu Yang, Chenlei Zhou, Yaoning Lian and Hengzhu Liu
Sensors 2023, 23(5), 2560; https://doi.org/10.3390/s23052560 - 25 Feb 2023
Cited by 16 | Viewed by 2578
Abstract
Coverage path planning (CPP) of multiple Dubins robots has been extensively applied in aerial monitoring, marine exploration, and search and rescue. Existing multi-robot coverage path planning (MCPP) research use exact or heuristic algorithms to address coverage applications. However, several exact algorithms always provide [...] Read more.
Coverage path planning (CPP) of multiple Dubins robots has been extensively applied in aerial monitoring, marine exploration, and search and rescue. Existing multi-robot coverage path planning (MCPP) research use exact or heuristic algorithms to address coverage applications. However, several exact algorithms always provide precise area division rather than coverage paths, and heuristic methods face the challenge of balancing accuracy and complexity. This paper focuses on the Dubins MCPP problem of known environments. Firstly, we present an exact Dubins multi-robot coverage path planning (EDM) algorithm based on mixed linear integer programming (MILP). The EDM algorithm searches the entire solution space to obtain the shortest Dubins coverage path. Secondly, a heuristic approximate credit-based Dubins multi-robot coverage path planning (CDM) algorithm is presented, which utilizes the credit model to balance tasks among robots and a tree partition strategy to reduce complexity. Comparison experiments with other exact and approximate algorithms demonstrate that EDM provides the least coverage time in small scenes, and CDM produces a shorter coverage time and less computation time in large scenes. Feasibility experiments demonstrate the applicability of EDM and CDM to a high-fidelity fixed-wing unmanned aerial vehicle (UAV) model. Full article
(This article belongs to the Topic Intelligent Systems and Robotics)
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19 pages, 3693 KiB  
Article
Dynamic Parameter Identification of Collaborative Robot Based on WLS-RWPSO Algorithm
by Minan Tang, Yaguang Yan, Bo An, Wenjuan Wang and Yaqi Zhang
Machines 2023, 11(2), 316; https://doi.org/10.3390/machines11020316 - 20 Feb 2023
Cited by 5 | Viewed by 2398
Abstract
Parameter identification of the dynamic model of collaborative robots is the basis of the development of collaborative robot motion state control, path tracking, state monitoring, fault diagnosis, and fault tolerance systems, and is one of the core contents of collaborative robot research. Aiming [...] Read more.
Parameter identification of the dynamic model of collaborative robots is the basis of the development of collaborative robot motion state control, path tracking, state monitoring, fault diagnosis, and fault tolerance systems, and is one of the core contents of collaborative robot research. Aiming at the identification of dynamic parameters of the collaborative robot, this paper proposes an identification algorithm based on weighted least squares and random weighted particle swarm optimization (WLS-RWPSO). Firstly, the dynamics mathematical model of the robot is established using the Lagrangian method, the dynamic parameters of the robot to be identified are determined, and the linear form of the dynamics model of the robot is derived taking into account the joint friction characteristics. Secondly, the weighted least squares method is used to obtain the initial solution of the parameters to be identified. Based on the traditional particle swarm optimization algorithm, a random weight particle swarm optimization algorithm is proposed for the local optimal problem to identify the dynamic parameters of the robot. Thirdly, the fifth-order Fourier series is designed as the excitation trajectory, and the original data collected by the sensor are denoised and smoothed by the Kalman filter algorithm. Finally, the experimental verification on a six-degree-of-freedom collaborative robot proves that the predicted torque obtained by the identification algorithm in this paper has a high degree of matching with the measured torque, and the established model can reflect the dynamic characteristics of the robot, effectively improving the identification accuracy. Full article
(This article belongs to the Topic Intelligent Systems and Robotics)
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26 pages, 1065 KiB  
Article
Damping Ratio Prediction for Redundant Cartesian Impedance-Controlled Robots Using Machine Learning Techniques
by José Patiño, Ángel Encalada-Dávila, José Sampietro, Christian Tutivén, Carlos Saldarriaga and Imin Kao
Mathematics 2023, 11(4), 1021; https://doi.org/10.3390/math11041021 - 17 Feb 2023
Cited by 1 | Viewed by 2550
Abstract
Implementing impedance control in Cartesian task space or directly at the joint level is a popular option for achieving desired compliance behavior for robotic manipulators performing tasks. The damping ratio is an important control criterion for modulating the dynamic response; however, tuning or [...] Read more.
Implementing impedance control in Cartesian task space or directly at the joint level is a popular option for achieving desired compliance behavior for robotic manipulators performing tasks. The damping ratio is an important control criterion for modulating the dynamic response; however, tuning or selecting this parameter is not easy, and can be even more complicated in cases where the system cannot be directly solved at the joint space level. Our study proposes a novel methodology for calculating the local optimal damping ratio value and supports it with results obtained from five different scenarios. We carried out 162 different experiments and obtained the values of the inertia, stiffness, and damping matrices for each experiment. Then, data preprocessing was carried out to select the most significant variables using different criteria, reducing the seventeen initial variables to only three. Finally, the damping ratio values were calculated (predicted) using automatic regression tools. In particular, five-fold cross-validation was used to obtain a more generalized model and to assess the forecasting performance. The results show a promising methodology capable of calculating and predicting control parameters for robotic manipulation tasks. Full article
(This article belongs to the Topic Intelligent Systems and Robotics)
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22 pages, 7819 KiB  
Article
Safety Verification of Multiple Industrial Robot Manipulators with Path Conflicts Using Model Checking
by Metin Ozkan, Zekeriyya Demirci, Özge Aslan and Ahmet Yazıcı
Machines 2023, 11(2), 282; https://doi.org/10.3390/machines11020282 - 13 Feb 2023
Cited by 2 | Viewed by 1552
Abstract
Software development for robotic systems is traditionally performed based on simulations, manual code implementation, and testing. However, this software development approach can cause safety issues in some scenarios, including multiple robots sharing a workspace. When different robots are executing individual planned tasks, they [...] Read more.
Software development for robotic systems is traditionally performed based on simulations, manual code implementation, and testing. However, this software development approach can cause safety issues in some scenarios, including multiple robots sharing a workspace. When different robots are executing individual planned tasks, they may collide when not adequately coordinated. Safety problems related to coordination between robots may not be encountered during testing, depending on timing, but may occur during the system’s operation. In this case, formal verification methods can provide a more reliable means to ensure the safety of robotic systems. This paper uses the formal method of model checking for the safety verification of multiple industrial robot manipulators with path conflicts. We give comparative results of two model-checking tools applied to a system with two robot manipulators. Whole workflows, from requirement specification to testing, are presented. Full article
(This article belongs to the Topic Intelligent Systems and Robotics)
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22 pages, 3878 KiB  
Article
An Artificial Neural Network Model for Project Effort Estimation
by Burcu Şengüneş and Nursel Öztürk
Systems 2023, 11(2), 91; https://doi.org/10.3390/systems11020091 - 9 Feb 2023
Cited by 5 | Viewed by 2635
Abstract
Estimating the project effort remains a challenge for project managers and effort estimators. In the early phases of a project, having a high level of uncertainty and lack of experience cause poor estimation of the required work. Especially for projects that produce a [...] Read more.
Estimating the project effort remains a challenge for project managers and effort estimators. In the early phases of a project, having a high level of uncertainty and lack of experience cause poor estimation of the required work. Especially for projects that produce a highly customized unique product for each customer, it is challenging to make estimations. Project effort estimation has been studied mainly for software projects in the literature. Currently, there has been no study on estimating effort in customized machine development projects to the best of our knowledge. This study aims to fill this gap in the literature regarding project effort estimation for customized machine development projects. Additionally, this study focused on a single phase of a project, the automation phase, in which the machine is automated according to customer-specific requirements. Therefore, the effort estimation of this phase is crucial. In some cases, this is the first time that the company has experienced the requirements specific to the customer. For this purpose, this study proposed a model to estimate how much work is required to automate a machine. Insufficient effort estimation is one of the main reasons behind project failures, and nowadays, researchers prefer more objective approaches such as machine learning over expert-based ones. This study also proposed an artificial neural network (ANN) model for this purpose. Data from past projects were used to train the proposed ANN model. The proposed model was tested on 11 real-life projects and showed promising results with acceptable prediction accuracy. Additionally, a desktop application was developed to make this system easier to use for project managers. Full article
(This article belongs to the Topic Intelligent Systems and Robotics)
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15 pages, 3601 KiB  
Article
EfferDeepNet: An Efficient Semantic Segmentation Method for Outdoor Terrain
by Yuhai Wei, Wu Wei and Yangbiao Zhang
Machines 2023, 11(2), 256; https://doi.org/10.3390/machines11020256 - 9 Feb 2023
Cited by 1 | Viewed by 1768
Abstract
The recognition of terrain and outdoor complex environments based on vision sensors is a key technology in practical robotics applications, and forms the basis of autonomous navigation and motion planning. While traditional machine learning methods can be applied to outdoor terrain recognition, their [...] Read more.
The recognition of terrain and outdoor complex environments based on vision sensors is a key technology in practical robotics applications, and forms the basis of autonomous navigation and motion planning. While traditional machine learning methods can be applied to outdoor terrain recognition, their recognition accuracy is low. In order to improve the accuracy of outdoor terrain recognition, methods based on deep learning are widely used. However, the network structure of deep learning methods is very complex, and the number of parameters is large, which cannot meet the actual operating requirements of of unmanned systems. Therefore, in order to solve the problems of poor real-time performance and low accuracy of deep learning algorithms for terrain recognition, this paper proposes the efficient EfferDeepNet network for pixel level terrain recognition in order to realize global perception of outdoor environment. First, this method uses convolution kernels with different sizes in the depthwise separable convolution (DSC) stage to extract more semantic feature information. Then, an attention mechanism is introduced to weight the acquired features, focusing on the key local feature areas. Finally, in order to avoid redundancy due to a large number of features and parameters in the model, this method uses a ghost module to make the network more lightweight. In addition, to solve the problem of pixel level terrain recognition having a negative effect on image boundary segmentation, the proposed method integrates an enhanced feature extraction network. Experimental results show that the proposed EfferDeepNet network can quickly and accurately perform global recognition and semantic segmentation of terrain in complex environments. Full article
(This article belongs to the Topic Intelligent Systems and Robotics)
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22 pages, 7730 KiB  
Article
Improved Chimpanzee Search Algorithm with Multi-Strategy Fusion and Its Application
by Hongda Wu, Fuxing Zhang and Teng Gao
Machines 2023, 11(2), 250; https://doi.org/10.3390/machines11020250 - 8 Feb 2023
Cited by 1 | Viewed by 1470
Abstract
An improved chimpanzee optimization algorithm incorporating multiple strategies (IMSChoA) is proposed to address the problems of initialized population boundary aggregation distribution, slow convergence speed, low precision, and proneness to fall into local optimality of the chimpanzee search algorithm. Firstly, the improved sine chaotic [...] Read more.
An improved chimpanzee optimization algorithm incorporating multiple strategies (IMSChoA) is proposed to address the problems of initialized population boundary aggregation distribution, slow convergence speed, low precision, and proneness to fall into local optimality of the chimpanzee search algorithm. Firstly, the improved sine chaotic mapping is used to initialize the population to solve the population boundary aggregation distribution problem. Secondly, a linear weighting factor and an adaptive acceleration factor are added to join the particle swarm idea and cooperate with the improved nonlinear convergence factor to balance the global search ability of the algorithm, accelerate the convergence of the algorithm, and improve the convergence accuracy. Finally, the sparrow elite mutation and Bernoulli chaos mapping strategy improved by adaptive change water wave factor are added to improve the ability of individuals to jump out of the local optimum. Through the comparative analysis of benchmark functions seeking optimization and the comparison of Wilcoxon rank sum statistical test seeking results, it can be seen that the IMSChoA optimization algorithm has stronger robustness and applicability. Further, the IMSChoA optimization algorithm is applied to two engineering examples to verify the superiority of the IMSChoA optimization algorithm in dealing with mechanical structure optimization design problems. Full article
(This article belongs to the Topic Intelligent Systems and Robotics)
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13 pages, 4212 KiB  
Article
Orientation Control System: Enhancing Aerial Maneuvers for Quadruped Robots
by Francesco Roscia, Andrea Cumerlotti, Andrea Del Prete, Claudio Semini and Michele Focchi
Sensors 2023, 23(3), 1234; https://doi.org/10.3390/s23031234 - 20 Jan 2023
Cited by 8 | Viewed by 3497
Abstract
For legged robots, aerial motions are the only option to overpass obstacles that cannot be circumvented with standard locomotion gaits. In these cases, the robot must perform a leap to either jump onto the obstacle or fly over it. However, these movements represent [...] Read more.
For legged robots, aerial motions are the only option to overpass obstacles that cannot be circumvented with standard locomotion gaits. In these cases, the robot must perform a leap to either jump onto the obstacle or fly over it. However, these movements represent a challenge, because, during the flight phase, the Center of Mass (CoM) cannot be controlled, and there is limited controllability over the orientation of the robot. This paper focuses on the latter issue and proposes an Orientation Control System (OCS), consisting of two rotating and actuated masses (flywheels or reaction wheels), to gain control authority on the orientation of the robot. Due to the conservation of angular momentum, the rotational velocity if the robot can be adjusted to steer the robot’s orientation, even when the robot has no contact with the ground. The axes of rotation of the flywheels are designed to be incident, leading to a compact orientation control system that is capable of controlling both roll and pitch angles, considering the different moments of inertia in the two directions. The concept was tested by means of simulations on the robot Solo12. Full article
(This article belongs to the Topic Intelligent Systems and Robotics)
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17 pages, 1173 KiB  
Article
Research on Multi-Objective Multi-Robot Task Allocation by Lin–Kernighan–Helsgaun Guided Evolutionary Algorithms
by Zhenqiang Zhang, Sile Ma and Xiangyuan Jiang
Mathematics 2022, 10(24), 4714; https://doi.org/10.3390/math10244714 - 12 Dec 2022
Cited by 5 | Viewed by 1691
Abstract
Multi-robot task allocation (MRTA) and route planning are crucial for a large-scale multi-robot system. In this paper, the problem is formulated to minimize the total energy consumption and overall task completion time simultaneously, with some constraints taken into consideration. To represent a solution, [...] Read more.
Multi-robot task allocation (MRTA) and route planning are crucial for a large-scale multi-robot system. In this paper, the problem is formulated to minimize the total energy consumption and overall task completion time simultaneously, with some constraints taken into consideration. To represent a solution, a novel one-chromosome representation technique is proposed, which eases the consequent genetic operations and the construction of the cost matrix. Lin–Kernighan–Helsgaun (LKH), a highly efficient sub-tour planner, is employed to generate prophet generation beforehand as well as guide the evolutionary direction during the proceeding of multi-objective evolutionary algorithms, aiming to promote convergence of the Pareto front. Numerical experiments on the benchmark show the LKH guidance mechanism is effective for two famous multi-objective evolutionary algorithms, namely multi-objective evolutionary algorithm based on decomposition (MOEA/D) and non-dominated sorting genetic algorithm (NSGA), of which LKH-guided NSGA exhibits the best performance on three predefined indicators, namely C-metric, HV, and Spacing, respectively. The generalization experiment on a multiple depots MRTA problem with constraints further demonstrates the effectiveness of the proposed approach for practical decision making. Full article
(This article belongs to the Topic Intelligent Systems and Robotics)
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24 pages, 8855 KiB  
Article
Algorithm for Determining the Types of Inverse Kinematics Solutions for Sequential Planar Robots and Their Representation in the Configuration Space
by Ivan Chavdarov and Bozhidar Naydenov
Algorithms 2022, 15(12), 469; https://doi.org/10.3390/a15120469 - 9 Dec 2022
Cited by 1 | Viewed by 2495
Abstract
The work defines in a new way the different types of solutions of the inverse kinematics (IK) problem for planar robots with a serial topology and presents an algorithm for solving it. The developed algorithm allows the finding of solutions for a wide [...] Read more.
The work defines in a new way the different types of solutions of the inverse kinematics (IK) problem for planar robots with a serial topology and presents an algorithm for solving it. The developed algorithm allows the finding of solutions for a wide range of robots by using a geometric approach, representing points in a polar coordinate system. Inverse kinematics, which is one of the most important, most studied and challenging problems in robotics, aims to calculate the values of the joint variables, given the desired position and orientation of the robot’s end effector. Configuration space is defined by joint angles and is the basis of most motion planning algorithms. Areas in the working and configuration space are generated that are reachable with different types of solutions. Programs are created that use the proposed algorithm for robots with two and three rotational degrees of freedom, and graphically present the results in the workspace and configuration space. The possibility of transitioning from one type of solution to another by passing through a singular configuration is discussed. The results are important for planning motions in the workspace and configuration space, as well as for the design and kinematic analysis of robots. Full article
(This article belongs to the Topic Intelligent Systems and Robotics)
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12 pages, 14747 KiB  
Article
Estimation of the Interaction Forces in a Compliant pHRI Gripper
by Francisco J. Ruiz-Ruiz, Cristina Urdiales and Jesús M. Gómez-de-Gabriel
Machines 2022, 10(12), 1128; https://doi.org/10.3390/machines10121128 - 28 Nov 2022
Cited by 1 | Viewed by 1491
Abstract
Physical human–robot interaction (pHRI) is an essential skill for robots expected to work with humans, such as assistive or rescue robots. However, due to hard safety and compliance constraints, pHRI is still underdeveloped in practice. Tactile sensing is vital for pHRI, as constant [...] Read more.
Physical human–robot interaction (pHRI) is an essential skill for robots expected to work with humans, such as assistive or rescue robots. However, due to hard safety and compliance constraints, pHRI is still underdeveloped in practice. Tactile sensing is vital for pHRI, as constant occlusions while grasping make it hard to rely on vision or range sensors alone. More specifically, measuring interaction forces in the gripper is crucial to avoid injuries, predict user intention and perform successful collaborative movements. This work exploits the inherent compliance of a gripper with four underactuated fingers which was previously designed by the authors and designed to manipulate human limbs. A new analytical model is proposed to calculate the external interaction forces by combining all finger forces, which are estimated by using the gripper proprioceptive sensor readings uniquely. An experimental evaluation of the method and an example application in a control system with active compliance have been included to evaluate performance. The results prove that the proposed finger arrangement offers good performance at measuring the lateral interaction forces and torque around the gripper’s Z-axis, providing a convenient and efficient way of implementing adaptive and compliant grasping for pHRI applications. Full article
(This article belongs to the Topic Intelligent Systems and Robotics)
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17 pages, 3196 KiB  
Article
An End-to-End Real-Time Lightweight Network for the Joint Segmentation of Optic Disc and Optic Cup on Fundus Images
by Zhijie Liu, Yuanqiong Chen, Xiaohua Xiang, Zhan Li, Bolin Liao and Jianfeng Li
Mathematics 2022, 10(22), 4288; https://doi.org/10.3390/math10224288 - 16 Nov 2022
Viewed by 1602
Abstract
Glaucoma is the second-most-blinding eye disease in the world and accurate segmentation of the optic disc (OD) and optic cup (OC) is essential for the diagnosis of glaucoma. To solve the problems of poor real-time performance, high algorithm complexity, and large memory consumption [...] Read more.
Glaucoma is the second-most-blinding eye disease in the world and accurate segmentation of the optic disc (OD) and optic cup (OC) is essential for the diagnosis of glaucoma. To solve the problems of poor real-time performance, high algorithm complexity, and large memory consumption of fundus segmentation algorithms, a lightweight segmentation algorithm, GlauNet, based on convolutional neural networks, is proposed. The algorithm designs an efficient feature-extraction network and proposes a multiscale boundary fusion (MBF) module, which greatly improves the segmentation efficiency of the algorithm while ensuring segmentation accuracy. Experiments show that the algorithm achieves Dice scores of 0.9701/0.8959, 0.9650/0.8621, and 0.9594/0.8795 on three publicly available datasets—Drishti-GS, RIM-ONE-r3, and REFUGE-train—for both the optic disc and the optic cup. The number of model parameters is only 0.8 M, and it only takes 13 ms to infer an 800 × 800 fundus image on a GTX 3070 GPU. Full article
(This article belongs to the Topic Intelligent Systems and Robotics)
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22 pages, 5579 KiB  
Article
Obstacles Avoidance for Mobile Robot Using Type-2 Fuzzy Logic Controller
by Mohammad Al-Mallah, Mohammad Ali and Mustafa Al-Khawaldeh
Robotics 2022, 11(6), 130; https://doi.org/10.3390/robotics11060130 - 16 Nov 2022
Cited by 11 | Viewed by 3376
Abstract
Intelligent mobile robots need to deal with different kinds of uncertainties in order to perform their tasks, such as tracking predefined paths and avoiding static and dynamic obstacles until reaching their destination. In this research, a Robotino® from Festo Company was used [...] Read more.
Intelligent mobile robots need to deal with different kinds of uncertainties in order to perform their tasks, such as tracking predefined paths and avoiding static and dynamic obstacles until reaching their destination. In this research, a Robotino® from Festo Company was used to reach a predefined target in different scenarios, autonomously, in a static and dynamic environment. A Type-2 fuzzy logic controller was used to guide and help Robotino® reach its predefined destination safely. The Robotino® collects data from the environment. The rules of the Type-2 fuzzy logic controller were built from human experience. They controlled the Robotino® movement, guiding it toward its goal by controlling its linear and angular velocities, preventing it from colliding obstacles at the same time, as well. The Takagi–Sugeno–Kang (TSK) algorithm was implemented. Real-time and simulation experimental results showed the capability and effectiveness of the proposed controller, especially in dealing with uncertainty problems. Full article
(This article belongs to the Topic Intelligent Systems and Robotics)
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17 pages, 4448 KiB  
Article
Deep-Learning-Based Cyber-Physical System Framework for Real-Time Industrial Operations
by Vatsal Maru, Saideep Nannapaneni, Krishna Krishnan and Ali Arishi
Machines 2022, 10(11), 1001; https://doi.org/10.3390/machines10111001 - 31 Oct 2022
Cited by 2 | Viewed by 2277
Abstract
Automation in the industry can improve production efficiency and human safety when performing complex and hazardous tasks. This paper presented an intelligent cyber-physical system framework incorporating image processing and deep-learning techniques to facilitate real-time operations. A convolutional neural network (CNN) is one of [...] Read more.
Automation in the industry can improve production efficiency and human safety when performing complex and hazardous tasks. This paper presented an intelligent cyber-physical system framework incorporating image processing and deep-learning techniques to facilitate real-time operations. A convolutional neural network (CNN) is one of the most widely used deep-learning techniques for image processing and object detection analysis. This paper used a variant of a CNN known as the faster R-CNN (R stands for the region proposals) for improved efficiency in object detection and real-time control analysis. The control action related to the detected object is exchanged with the actuation system within the cyber-physical system using a real-time data exchange (RTDE) protocol. We demonstrated the proposed intelligent CPS framework to perform object detection-based pick-and-place operations in real time as they are one of the most widely performed operations in quality control and industrial systems. The CPS consists of a camera system that is used for object detection, and the results are transmitted to a universal robot (UR5), which then picks the object and places it in the right location. Latency in communication is an important factor that can impact the quality of real-time operations. This paper discussed a Bayesian approach for uncertainty quantification of latency through the sampling–resampling approach, which can later be used to design a reliable communication framework for real-time operations. Full article
(This article belongs to the Topic Intelligent Systems and Robotics)
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16 pages, 4804 KiB  
Article
Binary Feature Description of 3D Point Cloud Based on Retina-like Sampling on Projection Planes
by Zhiqiang Yan, Hongyuan Wang, Xiang Liu, Qianhao Ning and Yinxi Lu
Machines 2022, 10(11), 984; https://doi.org/10.3390/machines10110984 - 27 Oct 2022
Cited by 1 | Viewed by 1445
Abstract
A binary feature description and registration algorithm for a 3D point cloud based on retina-like sampling on projection planes (RSPP) are proposed in this paper. The algorithm first projects the point cloud within the support radius around the key point to the XY, [...] Read more.
A binary feature description and registration algorithm for a 3D point cloud based on retina-like sampling on projection planes (RSPP) are proposed in this paper. The algorithm first projects the point cloud within the support radius around the key point to the XY, YZ, and XZ planes of the Local Reference Frame (LRF) and performs retina-like sampling on the projection plane. Then, the binarized Gaussian density weight values at the sampling points are calculated and encoded to obtain the RSPP descriptor. Finally, rough registration of point clouds is performed based on the RSPP descriptor, and the RANSAC algorithm is used to optimize the registration results. The performance of the proposed algorithm is tested on public point cloud datasets. The test results show that the RSPP-based point cloud registration algorithm has a good registration effect under no noise, 0.25 mr, and 0.5 mr Gaussian noise. The experimental results verify the correctness and robustness of the proposed registration method, which can provide theoretical and technical support for the 3D point cloud registration application. Full article
(This article belongs to the Topic Intelligent Systems and Robotics)
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17 pages, 3928 KiB  
Article
Deep Reinforcement Learning for Model Predictive Controller Based on Disturbed Single Rigid Body Model of Biped Robots
by Landong Hou, Bin Li, Weilong Liu, Yiming Xu, Shuhui Yang and Xuewen Rong
Machines 2022, 10(11), 975; https://doi.org/10.3390/machines10110975 - 26 Oct 2022
Cited by 1 | Viewed by 2265
Abstract
This paper modifies the single rigid body (SRB) model, and considers the swinging leg as the disturbances to the centroid acceleration and rotational acceleration of the SRB model. This paper proposes deep reinforcement learning (DRL)-based model predictive control (MPC) to resist the disturbances [...] Read more.
This paper modifies the single rigid body (SRB) model, and considers the swinging leg as the disturbances to the centroid acceleration and rotational acceleration of the SRB model. This paper proposes deep reinforcement learning (DRL)-based model predictive control (MPC) to resist the disturbances of the swinging leg. The DRL predicts the swing leg disturbances, and then MPC gives the optimal ground reaction forces according to the predicted disturbances. We use the proximal policy optimization (PPO) algorithm among the DRL methods since it is a very stable and widely applicable algorithm. It is an on-policy algorithm based on the actor–critic framework. The simulation results show that the improved SRB model and the PPO-based MPC method can accurately predict the disturbances of the swinging leg to the SRB model and resist the disturbance, making the locomotion more robust. Full article
(This article belongs to the Topic Intelligent Systems and Robotics)
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20 pages, 4571 KiB  
Article
A Fast Point Clouds Registration Algorithm Based on ISS-USC Feature for the 3D Laser Scanner
by Aihua Wu, Yinjia Ding, Jingfeng Mao and Xudong Zhang
Algorithms 2022, 15(10), 389; https://doi.org/10.3390/a15100389 - 21 Oct 2022
Cited by 4 | Viewed by 1941
Abstract
The point clouds registration is a key step in data processing for the 3D laser scanner to obtain complete information of the object surface, and there are many algorithms. In order to overcome the disadvantages of slow calculation speed and low accuracy of [...] Read more.
The point clouds registration is a key step in data processing for the 3D laser scanner to obtain complete information of the object surface, and there are many algorithms. In order to overcome the disadvantages of slow calculation speed and low accuracy of existing point clouds registration algorithms, a fast point clouds registration algorithm based on the improved voxel filter and ISS-USC feature is proposed. Firstly, the improved voxel filter is used for down-sampling to reduce the size of the original point clouds data. Secondly, the intrinsic shape signature (ISS) feature point detection algorithm is used to extra feature points from the down-sampled point clouds data, and then the unique shape context (USC) descriptor is calculated to describe the extracted feature points. Next, the improved random sampling consensus (RANSAC) algorithm is used for coarse registration to obtain the initial position. Finally, the iterative closest point (ICP) algorithm based on KD tree is used for fine registration, which realizes the transform from the point clouds scanned by the 3D laser scanner at different angles to the same coordinate system. Through comparing with other algorithms and the registration experiment of the VGA connector for monitor, the experimental results verify the effectiveness and feasibility of the proposed algorithm, and it has fastest registration speed while maintaining high registration accuracy. Full article
(This article belongs to the Topic Intelligent Systems and Robotics)
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15 pages, 3645 KiB  
Article
Evaluating the Influence of Data Entropy in the Use of a Smart Equipment for Traffic Management at Border Check Point
by Florin Rusca, Aura Rusca, Eugen Rosca, Catalin Coman, Stefan Burciu and Cristina Oprea
Machines 2022, 10(10), 937; https://doi.org/10.3390/machines10100937 - 16 Oct 2022
Cited by 1 | Viewed by 1297
Abstract
The transit through a Border Check Point of cargo vehicles supposes, in the case of the Romanian highway network, the carrying out of a process of weighing and verifying of transport licenses. The limited number of weighing equipment and the long duration of [...] Read more.
The transit through a Border Check Point of cargo vehicles supposes, in the case of the Romanian highway network, the carrying out of a process of weighing and verifying of transport licenses. The limited number of weighing equipment and the long duration of these processes cause large queues and long waiting times. A solution for these problems is to use smart equipment to identify the cargo vehicles and to separate the vehicles that require weighing from exempted ones. The separation process is made using external input data. The quality of received data can generate some dysfunctionality in the separation process. The discrete simulation model can be used to evaluate the influence of the uncertainty over the system serving parameters. A study case is developed for a real situation using real data collected from a Romanian Highway Traffic Control Center (HTMC). The results are used in the implementation of the new smart equipment in a Romanian Border Check Point. Full article
(This article belongs to the Topic Intelligent Systems and Robotics)
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29 pages, 16763 KiB  
Article
Robust Prescribed Trajectory Tracking Control of a Robot Manipulator Using Adaptive Finite-Time Sliding Mode and Extreme Learning Machine Method
by Mona Raoufi, Hamed Habibi, Amirmehdi Yazdani and Hai Wang
Robotics 2022, 11(5), 111; https://doi.org/10.3390/robotics11050111 - 15 Oct 2022
Cited by 4 | Viewed by 2434
Abstract
This study aims to provide a robust trajectory tracking controller which guarantees the prescribed performance of a robot manipulator, both in transient and steady-state modes, experiencing parametric uncertainties. The main core of the controller is designed based on the adaptive finite-time sliding mode [...] Read more.
This study aims to provide a robust trajectory tracking controller which guarantees the prescribed performance of a robot manipulator, both in transient and steady-state modes, experiencing parametric uncertainties. The main core of the controller is designed based on the adaptive finite-time sliding mode control (SMC) and extreme learning machine (ELM) methods to collectively estimate the parametric model uncertainties and enhance the quality of tracking performance. Accordingly, the global estimation with a fast convergence rate is achieved while the tracking error and the impact of chattering on the control input are mitigated significantly. Following the control design, the stability of the overall control system along with the finite-time convergence rate is proved, and the effectiveness of the proposed method is investigated via extensive simulation studies. The results of simulations confirm that the prescribed transient and steady-state performances are obtained with enough accuracy, fast convergence rate, robustness, and smooth control input which are all required for practical implementation and applications. Full article
(This article belongs to the Topic Intelligent Systems and Robotics)
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18 pages, 24450 KiB  
Article
Taikobot: A Full-Size and Free-Flying Humanoid Robot for Intravehicular Astronaut Assistance and Spacecraft Housekeeping
by Qi Zhang, Cheng Zhao, Li Fan and Yulin Zhang
Machines 2022, 10(10), 933; https://doi.org/10.3390/machines10100933 - 13 Oct 2022
Cited by 4 | Viewed by 3519
Abstract
This paper proposes a full-size and free-flying humanoid robot named Taikobot that aims to assist astronauts in a space station and maintain spacecrafts between human visits. Taikobot adopts a compact and lightweight (∼25 kg) design to work in microgravity, which also reduces launch [...] Read more.
This paper proposes a full-size and free-flying humanoid robot named Taikobot that aims to assist astronauts in a space station and maintain spacecrafts between human visits. Taikobot adopts a compact and lightweight (∼25 kg) design to work in microgravity, which also reduces launch costs and improves safety during human–robot collaboration. Taikobot’s anthropomorphic dual arm system and zero-g legs allow it to share a set of intravehicular human–machine interfaces. Unlike ground-walking robots, Taikobot maneuvers in a novel push–flight–park (PFP) strategy as an equivalent astronaut in a space station to maximize workspace and flexibility. We propose a PFP motion planning and control method based on centroidal dynamics and multi-contact model. Based on the proposed method, we carried out extensive simulations and verified the feasibility and advantages of the novel locomotion strategy. We also developed a prototype of Taikobot and carried out several ground experiments on typical scenarios where the robot collaborates with human astronauts. The experiments show that Taikobot can do some simple and repetitive tasks along with astronauts and has the potential to help astronauts improve their onboard working efficiency. Full article
(This article belongs to the Topic Intelligent Systems and Robotics)
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16 pages, 1856 KiB  
Article
Learning-Based Shared Control Using Gaussian Processes for Obstacle Avoidance in Teleoperated Robots
by Catalin Stefan Teodorescu, Keir Groves and Barry Lennox
Robotics 2022, 11(5), 102; https://doi.org/10.3390/robotics11050102 - 21 Sep 2022
Viewed by 1999
Abstract
Physically inspired models of the stochastic nature of the human-robot-environment interaction are generally difficult to derive from first principles, thus alternative data-driven approaches are an attractive option. In this article, Gaussian process regression is used to model a safe stop maneuver for a [...] Read more.
Physically inspired models of the stochastic nature of the human-robot-environment interaction are generally difficult to derive from first principles, thus alternative data-driven approaches are an attractive option. In this article, Gaussian process regression is used to model a safe stop maneuver for a teleoperated robot. In the proposed approach, a limited number of discrete experimental training data points are acquired to fit (or learn) a Gaussian process model, which is then used to predict the evolution of the process over a desired continuous range (or domain). A confidence measure for those predictions is used as a tuning parameter in a shared control algorithm, and it is demonstrated that it can be used to assist a human operator by providing (low-level) obstacle avoidance when they utilize the robot to carry out safety-critical tasks that involve remote navigation using the robot. The algorithm is personalized in the sense that it can be tuned to match the specific driving style of the person that is teleoperating the robot over a specific terrain. Experimental results demonstrate that with the proposed shared controller enabled, the human operator is able to more easily maneuver the robot in environments with (potentially dangerous) static obstacles, thus keeping the robot safe and preserving the original state of the surroundings. The future evolution of this work will be to apply this shared controller to mobile robots that are being deployed to inspect hazardous nuclear environments, ensuring that they operate with increased safety. Full article
(This article belongs to the Topic Intelligent Systems and Robotics)
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17 pages, 9647 KiB  
Article
Tableware Tidying-Up Robot System for Self-Service Restaurant–Detection and Manipulation of Leftover Food and Tableware-
by Deheng Zhu, Hiroaki Seki, Tokuo Tsuji and Tatsuhiro Hiramitsu
Sensors 2022, 22(18), 7006; https://doi.org/10.3390/s22187006 - 15 Sep 2022
Cited by 1 | Viewed by 2329
Abstract
In this study, an automated tableware tidying-up robot system was developed to tidy up tableware in a self-service restaurant with a large amount of tableware. This study focused on sorting and collecting tableware placed on trays detected by an RGB-D camera. Leftover food [...] Read more.
In this study, an automated tableware tidying-up robot system was developed to tidy up tableware in a self-service restaurant with a large amount of tableware. This study focused on sorting and collecting tableware placed on trays detected by an RGB-D camera. Leftover food was also treated with this robot system. The RGB-D camera efficiently detected the position and height of the tableware and whether there was leftover food or not by image processing. A parallel arm and robot hand mechanism was designed to realize the advantages of a low cost and high processing speed. Two types of rotation mechanisms were designed to realize the function of throwing away leftover food. The effectiveness of the camera detection system was verified through the experiments of tableware and leftover food detection. The effectiveness of the prototype robot and the rotation assist mechanism was verified through the experiments of grasping tableware, throwing away leftover food by two types of rotating mechanisms, collecting multiple tableware, and the sorting of overlapping tableware with multiple robots. Full article
(This article belongs to the Topic Intelligent Systems and Robotics)
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17 pages, 7225 KiB  
Article
A Study on Data Analysis for Improving Driving Safety in Field Operational Test (FOT) of Autonomous Vehicles
by Seok-San Shin, Ho-Joon Kang and Seong-Jin Kwon
Machines 2022, 10(9), 784; https://doi.org/10.3390/machines10090784 - 7 Sep 2022
Cited by 4 | Viewed by 2084
Abstract
In this study, an autonomous driving test was conducted from the perspective of FOT (field operational test). For data analysis and improvement methods, scenarios for FOT were classified and defined by considering autonomous driving level (SAE J3016) and the viewpoints of the vehicle, [...] Read more.
In this study, an autonomous driving test was conducted from the perspective of FOT (field operational test). For data analysis and improvement methods, scenarios for FOT were classified and defined by considering autonomous driving level (SAE J3016) and the viewpoints of the vehicle, driver, road, environment, etc. To obtain data from FOT, performance indicators were selected, a data collection environment was implemented in the test cases, and driving roads were selected to obtain driving data from the vehicle while it was driven on an actual road. In the pilot FOT course, data were collected in various driving situations using a test vehicle, and the effect of autonomous driving-related functions on improving driving safety was studied through data analysis of discovered major events. Full article
(This article belongs to the Topic Intelligent Systems and Robotics)
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16 pages, 9880 KiB  
Article
Adaptive Neural-PID Visual Servoing Tracking Control via Extreme Learning Machine
by Junqi Luo, Liucun Zhu, Ning Wu, Mingyou Chen, Daopeng Liu, Zhenyu Zhang and Jiyuan Liu
Machines 2022, 10(9), 782; https://doi.org/10.3390/machines10090782 - 7 Sep 2022
Cited by 3 | Viewed by 2071
Abstract
The vision-guided robot is intensively embedded in modern industry, but it is still a challenge to track moving objects in real time accurately. In this paper, a hybrid adaptive control scheme combined with an Extreme Learning Machine (ELM) and proportional–integral–derivative (PID) is proposed [...] Read more.
The vision-guided robot is intensively embedded in modern industry, but it is still a challenge to track moving objects in real time accurately. In this paper, a hybrid adaptive control scheme combined with an Extreme Learning Machine (ELM) and proportional–integral–derivative (PID) is proposed for dynamic visual tracking of the manipulator. The scheme extracts line features on the image plane based on a laser-camera system and determines an optimal control input to guide the robot, so that the image features are aligned with their desired positions. The observation and state–space equations are first determined by analyzing the motion features of the camera and the object. The system is then represented as an autoregressive moving average with extra input (ARMAX) and a valid estimation model. The adaptive predictor estimates online the relevant 3D parameters between the camera and the object, which are subsequently used to calculate the system sensitivity of the neural network. The ELM–PID controller is designed for adaptive adjustment of control parameters, and the scheme was validated on a physical robot platform. The experimental results showed that the proposed method’s vision-tracking control displayed superior performance to pure P and PID controllers. Full article
(This article belongs to the Topic Intelligent Systems and Robotics)
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14 pages, 6708 KiB  
Article
Utilisation of Initialised Observation Scheme for Multi-Joint Robotic Arm in Lyapunov-Based Adaptive Control Strategy
by Mohammad Soleimani Amiri and Rizauddin Ramli
Mathematics 2022, 10(17), 3126; https://doi.org/10.3390/math10173126 - 31 Aug 2022
Cited by 3 | Viewed by 2087
Abstract
In this paper, we present a modelling, dynamic analysis, and controller tuning comparison for a five-degree-of-freedom (DoF) multi-joint robotic arm based on the Lyapunov-based Adaptive Controller (LAC). In most pick-and-place applications of robotic arms, it is essential to control the end-effector trajectory to [...] Read more.
In this paper, we present a modelling, dynamic analysis, and controller tuning comparison for a five-degree-of-freedom (DoF) multi-joint robotic arm based on the Lyapunov-based Adaptive Controller (LAC). In most pick-and-place applications of robotic arms, it is essential to control the end-effector trajectory to reach a precise target position. The kinematic solution of the 5-DoF robotic arm has been determined by the Lagrangian technique, and the mathematical model of each joint has been obtained in the range of motion condition. The Proportional-Integral-Derivative (PID) control parameters of the LAC have been determined by the Lyapunov stability approach and are initialised by four observation methods based on the obtained transfer function. The effectiveness of the initialised controller’s parameters is compared by a unit step response as the desired input of the controller system. As a result, the average error (AE) for Ziegler–Nichols is 6.6%, 83%, and 53% lower than for Pettit & Carr, Chau, and Bucz. The performance of LAC for the robotic arm model is validated in a virtual 3D model under a robot operating system environment. The results of root mean square error by LAC are 0.021 (rad) and 0.025 (rad) for joint 1 and joint 2, respectively, which indicate the efficiency of the proposed LAC strategy in reaching the predetermined trajectory and the potential of minimizing the controller tuning complexity. Full article
(This article belongs to the Topic Intelligent Systems and Robotics)
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22 pages, 5270 KiB  
Article
VLP Landmark and SLAM-Assisted Automatic Map Calibration for Robot Navigation with Semantic Information
by Yiru Wang, Babar Hussain and Chik Patrick Yue
Robotics 2022, 11(4), 84; https://doi.org/10.3390/robotics11040084 - 21 Aug 2022
Cited by 2 | Viewed by 3062
Abstract
With the rapid development of robotics and in-depth research of automatic navigation technology, mobile robots have been applied in a variety of fields. Map construction is one of the core research focuses of mobile robot development. In this paper, we propose an autonomous [...] Read more.
With the rapid development of robotics and