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Robotic Systems and Automatic Control: Mathematical Models, Technologies, Applications and Challenges

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensors and Robotics".

Deadline for manuscript submissions: 30 August 2024 | Viewed by 30517

Special Issue Editor


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Guest Editor
Department of Information Engineering, Polytechnic University of Marche, 60131 Ancona, Italy
Interests: marine robotics; educational robotics; STEM; SLAM; photogrammetry; multi agents systems
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The use of complex robots in challenging and unusual environments has increased remarkably in the last decade. This tendency has been even more relevant in education, serious gaming for training and risk awareness, connected industrial environments, cyber-physical systems, and digital robotic twinning of complex distributed systems, where robots have shown to be a perfect tool for the new digital era.

Previously, robots and their automation techniques have been mainly used as mechatronic elements to accomplish specific tasks. Consolidated sensors, identification methodologies and modelling theories are insufficient for present-day robotics.

Recent progress in robotics and automatic control, with innovation in computational intelligence or its use for identifying processes, has seen the development of remarkable and powerful theoretical tools for future robotic and distributed sensor networks designers.

This Special Issue aims to create a collection of papers that summarize the state of the art in advances to face the new robotics needs and complex system sense strategies. Formal and reliable approaches towards intelligent robotics should be tested in real applications or case studies. Experiences in machine learning, computer vision, or any other specific subject of computational intelligence tested in real or simulated robots will be considered.

The Special Issue provides an advanced forum for the science and technology of innovative sensors and their applications in control and automation. The aim is to encourage scientists to publish their experimental and theoretical results in as much detail as possible. The full experimental details must be provided so that the results can be reproduced.

Dr. David Scaradozzi
Guest Editor

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Robotics
  • Complex systems
  • Innovative sensors for robotics
  • System identification applied to robots and complex robotic systems
  • Modelling robotic systems
  • Robotic intervention and measurement in challenging environments
  • Robotic sensing systems

Published Papers (15 papers)

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Research

13 pages, 3540 KiB  
Article
Liquid-Driven Microinjection System for Precise Fundus Injection
by Shiyu Xu, Bo Hu, Rongxin Liu, Xin Zhao and Mingzhu Sun
Sensors 2024, 24(7), 2140; https://doi.org/10.3390/s24072140 - 27 Mar 2024
Viewed by 500
Abstract
Microinjection is usually applied to the treatment of some retinal disorders, such as retinal vein cannulation and displaced submacular hemorrhage. Currently, the microinjection procedure is usually performed by using the viscous fluid control of a standard vitrectomy system, which applies a fixed air [...] Read more.
Microinjection is usually applied to the treatment of some retinal disorders, such as retinal vein cannulation and displaced submacular hemorrhage. Currently, the microinjection procedure is usually performed by using the viscous fluid control of a standard vitrectomy system, which applies a fixed air pressure through foot pedal activation. The injection process with the fixed pressure is uncontrollable and lacks feedback, the high flow rate of the injected drug may cause damage to the fundus tissue. In this paper, a liquid-driven microinjection system with a flow sensor is designed and developed specifically for fundus injection. In addition, a PID sliding mode control (SMC) method is proposed to achieve precise injection in the injection system. The experimental results of fundus simulation injection demonstrate that the microinjection system meets the requirements of fundus injection and reduces the impact of the injection process on the fundus tissue. Full article
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17 pages, 5144 KiB  
Article
Trampoline Stiffness Estimation by Using Robotic System for Quantitative Evaluation of Jumping Exercises
by Gunseok Park, Seung-Hwan Choi, Chang-Hyun Kim, Min Young Kim and Suwoong Lee
Sensors 2023, 23(24), 9645; https://doi.org/10.3390/s23249645 - 6 Dec 2023
Viewed by 1200
Abstract
Trampolines are recognized as a valuable tool in exercise and rehabilitation due to their unique properties like elasticity, rebound force, low-impact exercise, and enhancement of posture, balance, and cardiopulmonary function. To quantitatively assess the effects of trampoline exercises, it is essential to estimate [...] Read more.
Trampolines are recognized as a valuable tool in exercise and rehabilitation due to their unique properties like elasticity, rebound force, low-impact exercise, and enhancement of posture, balance, and cardiopulmonary function. To quantitatively assess the effects of trampoline exercises, it is essential to estimate factors such as stiffness, elements influencing jump dynamics, and user safety. Previous studies assessing trampoline characteristics had limitations in performing repetitive experiments at various locations on the trampoline. Therefore, this research introduces a robotic system equipped with foot-shaped jigs to evaluate trampoline stiffness and quantitatively measure exercise effects. This system, through automated, repetitive movements at various locations on the trampoline, accurately measures the elastic coefficient and vertical forces. The robot maneuvers based on the coordinates of the trampoline, as determined by its torque and position sensors. The force sensor measures data related to the force exerted, along with the vertical force data at X, Y, and Z coordinates. The model’s accuracy was evaluated using linear regression based on Hooke’s Law, with Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and Correlation Coefficient Squared (R-squared) metrics. In the analysis including only the distance between X and the foot-shaped jigs, the average MAE, RMSE, and R-squared values were 17.9702, 21.7226, and 0.9840, respectively. Notably, expanding the model to include distances in X, Y, and between the foot-shaped jigs resulted in a decrease in MAE to 15.7347, RMSE to 18.8226, and an increase in R-squared to 0.9854. The integrated model, including distances in X, Y, and between the foot-shaped jigs, showed improved predictive capability with lower MAE and RMSE and higher R-squared, indicating its effectiveness in more accurately predicting trampoline dynamics, vital in fitness and rehabilitation fields. Full article
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17 pages, 1591 KiB  
Article
Cautious Bayesian Optimization: A Line Tracker Case Study
by Vicent Girbés-Juan, Joaquín Moll, Antonio Sala and Leopoldo Armesto
Sensors 2023, 23(16), 7266; https://doi.org/10.3390/s23167266 - 18 Aug 2023
Viewed by 804
Abstract
In this paper, a procedure for experimental optimization under safety constraints, to be denoted as constraint-aware Bayesian Optimization, is presented. The basic ingredients are a performance objective function and a constraint function; both of them will be modeled as Gaussian processes. We incorporate [...] Read more.
In this paper, a procedure for experimental optimization under safety constraints, to be denoted as constraint-aware Bayesian Optimization, is presented. The basic ingredients are a performance objective function and a constraint function; both of them will be modeled as Gaussian processes. We incorporate a prior model (transfer learning) used for the mean of the Gaussian processes, a semi-parametric Kernel, and acquisition function optimization under chance-constrained requirements. In this way, experimental fine-tuning of a performance objective under experiment-model mismatch can be safely carried out. The methodology is illustrated in a case study on a line-follower application in a CoppeliaSim environment. Full article
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13 pages, 5459 KiB  
Communication
Obstacle Detection in Infrared Navigation for Blind People and Mobile Robots
by Ioannis Papagianopoulos, Gilbert De Mey, Andrzej Kos, Boguslaw Wiecek and Vasilis Chatziathasiou
Sensors 2023, 23(16), 7198; https://doi.org/10.3390/s23167198 - 16 Aug 2023
Cited by 1 | Viewed by 1168
Abstract
The paper is a continuation of the authors’ work intended for infrared navigation for blind people and mobile robots. This concerns the detection of obstacles in the person’s or mobile robot’s trajectory, in particular, the detection of corners. The temperature distribution of a [...] Read more.
The paper is a continuation of the authors’ work intended for infrared navigation for blind people and mobile robots. This concerns the detection of obstacles in the person’s or mobile robot’s trajectory, in particular, the detection of corners. The temperature distribution of a building’s internal wall near a corner has been investigated. Due to geometry, more heat will be transferred by conduction so that inside the building, the temperature on the wall will be decreasing towards a corner. The problem will be investigated theoretically and numerically, and the results are confirmed by experimental measurements. The purpose of this research is to help blind people by equipping them with a small infrared camera that warns them when they are approaching a corner inside a building. The same aim is addressed to mobile robots. Full article
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30 pages, 9253 KiB  
Article
Design of A Finite-Time Adaptive Controller for Image-Based Uncalibrated Visual Servo Systems with Uncertainties in Robot and Camera Models
by Zhuoqun Zhao, Jiang Wang and Hui Zhao
Sensors 2023, 23(16), 7133; https://doi.org/10.3390/s23167133 - 11 Aug 2023
Cited by 1 | Viewed by 820
Abstract
Aiming at the time-varying uncertainties of robot and camera models in IBUVS (image-based uncalibrated visual servo) systems, a finite-time adaptive controller is proposed based on the depth-independent Jacobian matrix. Firstly, the adaptive law of depth parameters, kinematic parameters, and dynamic parameters is proposed [...] Read more.
Aiming at the time-varying uncertainties of robot and camera models in IBUVS (image-based uncalibrated visual servo) systems, a finite-time adaptive controller is proposed based on the depth-independent Jacobian matrix. Firstly, the adaptive law of depth parameters, kinematic parameters, and dynamic parameters is proposed for the uncertainty of a robot model and a camera model. Secondly, a finite-time adaptive controller is designed by using a nonlinear proportional differential plus a dynamic feedforward compensation structure. By applying a continuous non-smooth nonlinear function to the feedback error, the control quality of the closed-loop system is improved, and the desired trajectory of the image is tracked in finite time. Finally, using the Lyapunov stability theory and the finite-time stability theory, the global finite-time stability of the closed-loop system is proven. The experimental results show that the proposed controller can not only adapt to the changes in the EIH and ETH visual configurations but also adapt to the changes in the relative pose of feature points and the camera’s relative pose parameters. At the same time, the convergence rate near the equilibrium point is improved, and the controller has good dynamic stability. Full article
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14 pages, 4968 KiB  
Article
Design, Construction and Control of a Manipulator Driven by Pneumatic Artificial Muscles
by Željko Šitum, Srečko Herceg, Nenad Bolf and Željka Ujević Andrijić
Sensors 2023, 23(2), 776; https://doi.org/10.3390/s23020776 - 10 Jan 2023
Cited by 4 | Viewed by 2087
Abstract
This paper describes the design, construction and experimental testing of a single-joint manipulator arm actuated by pneumatic artificial muscles (PAMs) for the tasks of transporting and sorting work pieces. An antagonistic muscle pair is used in a rotational sense to produce a required [...] Read more.
This paper describes the design, construction and experimental testing of a single-joint manipulator arm actuated by pneumatic artificial muscles (PAMs) for the tasks of transporting and sorting work pieces. An antagonistic muscle pair is used in a rotational sense to produce a required torque on a pulley. The concept, operating principle and elementary properties of pneumatic muscle actuators are explained. Different conceptions of the system realizations are analyzed using the morphological-matrix conceptual design framework and top-rated solution was practically realized. A simplified, control-oriented mathematical model of the manipulator arm driven by PAMs and controlled with a proportional control valve is derived. The model is then used for a controller design process. Fluidic muscles have great potential for industrial applications and assembly automation to actuate new types of robots and manipulators. Their characteristics, such as compactness, high strength, high power-to-weight ratio, inherent safety and simplicity, are worthy features for advanced manipulation systems. The experiments were carried out on a practically realized manipulator actuated by a pair of muscle actuators set into an antagonistic configuration. The setup also includes an original solution for the subsystem to add work pieces in the working space of the manipulator. Full article
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21 pages, 2091 KiB  
Article
A Two-Step Method for Dynamic Parameter Identification of Indy7 Collaborative Robot Manipulator
by Meseret Tadese, Nabih Pico, Sungwon Seo and Hyungpil Moon
Sensors 2022, 22(24), 9708; https://doi.org/10.3390/s22249708 - 11 Dec 2022
Cited by 6 | Viewed by 1860
Abstract
Accurate dynamic model is critical for collaborative robots to achieve satisfactory performance in model-based control or other applications such as dynamic simulation and external torque estimation. Such dynamic models are frequently restricted to identifying important system parameters and compensating for nonlinear terms. Friction, [...] Read more.
Accurate dynamic model is critical for collaborative robots to achieve satisfactory performance in model-based control or other applications such as dynamic simulation and external torque estimation. Such dynamic models are frequently restricted to identifying important system parameters and compensating for nonlinear terms. Friction, as a primary nonlinear element in robotics, has a significant impact on model accuracy. In this paper, a reliable dynamic friction model, which incorporates the influence of temperature fluctuation on the robot joint friction, is utilized to increase the accuracy of identified dynamic parameters. First, robot joint friction is investigated. Extensive test series are performed in the full velocity operating range at temperatures ranging from 19 °C to 51 °C to investigate friction dependency on joint module temperature. Then, dynamic parameter identification is performed using an inverse dynamics identification model and weighted least squares regression constrained to the feasible space, guaranteeing the optimal solution. Using the identified friction model parameters, the friction torque is computed for measured robot joint velocity and temperature. Friction torque is subtracted from the measured torque, and a non-friction torque is used to identify dynamic parameters. Finally, the proposed notion is validated experimentally on the Indy7 collaborative robot manipulator, and the results show that the dynamic model with parameters identified using the proposed method outperforms the dynamic model with parameters identified using the conventional method in tracking measured torque, with a relative improvement of up to 70.37%. Full article
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13 pages, 5895 KiB  
Article
Development of a Multi-Layer Marking Toolkit for Layout-Printing Automation at Construction Sites
by Eun Soo Park, Hee Chang Seo and An Yong Lee
Sensors 2022, 22(13), 4822; https://doi.org/10.3390/s22134822 - 25 Jun 2022
Cited by 3 | Viewed by 1802
Abstract
In this study, the development of a multi-layer marking toolkit was investigated to improve construction quality and mitigate the problem of irregular designs in the layout-printing work performed at construction sites. The quality of conventional layout-printing work is dependent on the skill of [...] Read more.
In this study, the development of a multi-layer marking toolkit was investigated to improve construction quality and mitigate the problem of irregular designs in the layout-printing work performed at construction sites. The quality of conventional layout-printing work is dependent on the skill of the worker, and construction quality can suffer owing to inconsistencies in drawings resulting from human error. In this study, these problems were analyzed, and a construction-site-layout-marking toolkit apparatus and mechanical unit, with a structure that allowed for multi-layer installation for automated implementation at construction sites, were developed. The marking toolkit and mechanical unit with the multi-layer structure were developed in a modular form so that each module can operate independently. Furthermore, each module was developed in manual mode to improve the system by acquiring information on the movement of the marking toolkit and multi-layer structure. Additionally, data on the layout-printing method was developed by connecting the system via Ethernet and operating a wireless joystick. Finally, experiments were performed on a road surface covered with B4 paper and concrete panels to confirm the operational feasibility of the system, which was developed to operate manually. Full article
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29 pages, 6518 KiB  
Article
System Identification and Nonlinear Model Predictive Control with Collision Avoidance Applied in Hexacopters UAVs
by Luis F. Recalde, Bryan S. Guevara, Christian P. Carvajal, Victor H. Andaluz, José Varela-Aldás and Daniel C. Gandolfo
Sensors 2022, 22(13), 4712; https://doi.org/10.3390/s22134712 - 22 Jun 2022
Cited by 6 | Viewed by 3076
Abstract
Accurate trajectory tracking is a critical property of unmanned aerial vehicles (UAVs) due to system nonlinearities, under-actuated properties and constraints. Specifically, the use of unmanned rotorcrafts with accuracy trajectory tracking controllers in dynamic environments has the potential to improve the fields of environment [...] Read more.
Accurate trajectory tracking is a critical property of unmanned aerial vehicles (UAVs) due to system nonlinearities, under-actuated properties and constraints. Specifically, the use of unmanned rotorcrafts with accuracy trajectory tracking controllers in dynamic environments has the potential to improve the fields of environment monitoring, safety, search and rescue, border surveillance, geology and mining, agriculture industry, and traffic control. Monitoring operations in dynamic environments produce significant complications with respect to accuracy and obstacles in the surrounding environment and, in many cases, it is difficult to perform even with state-of-the-art controllers. This work presents a nonlinear model predictive control (NMPC) with collision avoidance for hexacopters’ trajectory tracking in dynamic environments, as well as shows a comparative study between the accuracies of the Euler–Lagrange formulation and the dynamic mode decomposition (DMD) models in order to find the precise representation of the system dynamics. The proposed controller includes limits on the maneuverability velocities, system dynamics, obstacles and the tracking error in the optimization control problem (OCP). In order to show the good performance of this control proposal, computational simulations and real experiments were carried out using a six rotary-wind unmanned aerial vehicle (hexacopter—DJI MATRICE 600). The experimental results prove the good performance of the predictive scheme and its ability to regenerate the optimal control policy. Simulation results expand the proposed controller in simulating highly dynamic environments that showing the scalability of the controller. Full article
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22 pages, 5672 KiB  
Article
CFHBA-PID Algorithm: Dual-Loop PID Balancing Robot Attitude Control Algorithm Based on Complementary Factor and Honey Badger Algorithm
by Jianan Lin, Rongjia Zheng, Yirong Zhang, Jinkai Feng, Wei Li and Kaiqing Luo
Sensors 2022, 22(12), 4492; https://doi.org/10.3390/s22124492 - 14 Jun 2022
Cited by 9 | Viewed by 2287
Abstract
The PID control algorithm for balancing robot attitude control suffers from the problem of difficult parameter tuning. Previous studies have proposed using metaheuristic algorithms to tune the PID parameters. However, traditional metaheuristic algorithms are subject to the criticism of premature convergence and the [...] Read more.
The PID control algorithm for balancing robot attitude control suffers from the problem of difficult parameter tuning. Previous studies have proposed using metaheuristic algorithms to tune the PID parameters. However, traditional metaheuristic algorithms are subject to the criticism of premature convergence and the possibility of falling into local optimum solutions. Therefore, the present paper proposes a CFHBA-PID algorithm for balancing robot Dual-loop PID attitude control based on Honey Badger Algorithm (HBA) and CF-ITAE. On the one hand, HBA maintains a sufficiently large population diversity throughout the search process and employs a dynamic search strategy for balanced exploration and exploitation, effectively avoiding the problems of classical intelligent optimization algorithms and serving as a global search. On the other hand, a novel complementary factor (CF) is proposed to complement integrated time absolute error (ITAE) with the overshoot amount, resulting in a new rectification indicator CF-ITAE, which balances the overshoot amount and the response time during parameter tuning. Using balancing robot as the experimental object, HBA-PID is compared with AOA-PID, WOA-PID, and PSO-PID, and the results demonstrate that HBA-PID outperforms the other three algorithms in terms of overshoot amount, stabilization time, ITAE, and convergence speed, proving that the algorithm combining HBA with PID is better than the existing mainstream algorithms. The comparative experiments using CF prove that CFHBA-PID is able to effectively control the overshoot amount in attitude control. In conclusion, the CFHBA-PID algorithm has great control and significant results when applied to the balancing robot. Full article
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24 pages, 9688 KiB  
Article
Task-Oriented Evaluation of the Feasible Kinematic Directional Capabilities for Robot Machining
by Saša Stradovnik and Aleš Hace
Sensors 2022, 22(11), 4267; https://doi.org/10.3390/s22114267 - 3 Jun 2022
Cited by 5 | Viewed by 2034
Abstract
Performing the machining of complex surfaces can be a challenging task for a robot, especially in terms of collaborative robotics, where the available motion capabilities are greatly reduced in comparison with conventional industrial robot arms. It is necessary to evaluate these capabilities prior [...] Read more.
Performing the machining of complex surfaces can be a challenging task for a robot, especially in terms of collaborative robotics, where the available motion capabilities are greatly reduced in comparison with conventional industrial robot arms. It is necessary to evaluate these capabilities prior to task execution, for which we need efficient algorithms, especially in the case of flexible robot applications. To provide accurate and physically consistent information about the maximum kinematic capabilities while considering the requirements of the task, an approach called the Decomposed Twist Feasibility (DTF) method is proposed in this study. The evaluation of the maximum feasible end-effector velocity is based on the idea of decomposition into the linear and angular motion capabilities, considering a typical robot machining task with synchronous linear and angular motion. The proposed DTF method is presented by the well-known manipulability polytope concept. Unlike the existing methods that estimate the kinematic performance capabilities in arbitrarily weighted twist space, or separately in the translation and the rotation subspace, our approach offers an accurate and simple solution for the determination of the total kinematic performance capabilities, which is often highly required, especially in the case of robot machining tasks. The numerical results obtained in this study show the effectiveness of the proposed approach. Moreover, the proposed DTF method could represent suitable kinematic performance criteria for the optimal placement of predefined tasks within the robot workspace. Full article
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19 pages, 3212 KiB  
Article
Implementation of Omni-D Tele-Presence Robot Using Kalman Filter and Tricon Ultrasonic Sensors
by Hassan Tariq, Muhammad Rashid, Asfa Javed, Muhammad Aaqib Riaz, Mohammed Sinky and Muhammad Yousuf Irfan Zia
Sensors 2022, 22(10), 3948; https://doi.org/10.3390/s22103948 - 23 May 2022
Cited by 2 | Viewed by 2269
Abstract
The tele-presence robot is designed to set forth an economic solution to facilitate day-to-day normal activities in almost every field. There are several solutions to design tele-presence robots, e.g., Skype and team viewer, but it is pretty inappropriate to use Skype and extra [...] Read more.
The tele-presence robot is designed to set forth an economic solution to facilitate day-to-day normal activities in almost every field. There are several solutions to design tele-presence robots, e.g., Skype and team viewer, but it is pretty inappropriate to use Skype and extra hardware. Therefore, in this article, we have presented a robust implementation of the tele-presence robot. Our proposed omnidirectional tele-presence robot consists of (i) Tricon ultrasonic sensors, (ii) Kalman filter implementation and control, and (iii) integration of our developed WebRTC-based application with the omnidirectional tele-presence robot for video transmission. We present a new algorithm to encounter the sensor noise with the least number of sensors for the estimation of Kalman filter. We have simulated the complete model of robot in Simulink and Matlab for the tough paths and critical hurdles. The robot successfully prevents the collision and reaches the destination. The mean errors for the estimation of position and velocity are 5.77% and 2.04%. To achieve efficient and reliable video transmission, the quality factors such as resolution, encoding, average delay and throughput are resolved using the WebRTC along with the integration of the communication protocols. To protect the data transmission, we have implemented the SSL protocol and installed it on the server. We tested three different cases of video resolutions (i.e., 320×280, 820×460 and 900×590) for the performance evaluation of the video transmission. For the highest resolution, our TPR takes 3.5 ms for the encoding, and the average delay is 2.70 ms with 900 × 590 pixels. Full article
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16 pages, 2043 KiB  
Article
Deep Q-Learning in Robotics: Improvement of Accuracy and Repeatability
by Marius Sumanas, Algirdas Petronis, Vytautas Bucinskas, Andrius Dzedzickis, Darius Virzonis and Inga Morkvenaite-Vilkonciene
Sensors 2022, 22(10), 3911; https://doi.org/10.3390/s22103911 - 21 May 2022
Cited by 11 | Viewed by 3331
Abstract
Recent industrial robotics covers a broad part of the manufacturing spectrum and other human everyday life applications; the performance of these devices has become increasingly important. Positioning accuracy and repeatability, as well as operating speed, are essential in any industrial robotics application. Robot [...] Read more.
Recent industrial robotics covers a broad part of the manufacturing spectrum and other human everyday life applications; the performance of these devices has become increasingly important. Positioning accuracy and repeatability, as well as operating speed, are essential in any industrial robotics application. Robot positioning errors are complex due to the extensive combination of their sources and cannot be compensated for using conventional methods. Some robot positioning errors can be compensated for only using machine learning (ML) procedures. Reinforced machine learning increases the robot’s positioning accuracy and expands its implementation capabilities. The provided methodology presents an easy and focused approach for industrial in situ robot position adjustment in real-time during production setup or readjustment cases. The scientific value of this approach is a methodology using an ML procedure without huge external datasets for the procedure and extensive computing facilities. This paper presents a deep q-learning algorithm applied to improve the positioning accuracy of an articulated KUKA youBot robot during operation. A significant improvement of the positioning accuracy was achieved approximately after 260 iterations in the online mode and initial simulation of the ML procedure. Full article
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17 pages, 3774 KiB  
Article
Singular Configuration Analysis and Singularity Avoidance with Application in an Intelligent Robotic Manipulator
by Helin Wang, Ziqiang Zhou, Xianyou Zhong and Qijun Chen
Sensors 2022, 22(3), 1239; https://doi.org/10.3390/s22031239 - 6 Feb 2022
Cited by 5 | Viewed by 2777
Abstract
Recently, robotic sensor systems have gained more attention annually in complex system sense strategies. The robotic sensors sense the information from itself and the environment, and fuse information for the use of perception, decision, planning, and control. As an important supplement to traditional [...] Read more.
Recently, robotic sensor systems have gained more attention annually in complex system sense strategies. The robotic sensors sense the information from itself and the environment, and fuse information for the use of perception, decision, planning, and control. As an important supplement to traditional industrial robots, co-bots (short for co-working robots) play an increasingly vital role in helping small and medium-sized enterprises realize intelligent manufacturing. They have high flexibility and safety so that they can assist humans to complete highly repetitive and high-precision work. In order to maintain robot safe operation in the increasing complex working environment and human–computer intelligent interactive control, this paper is concerned with the problem of applicant accuracy analysis and singularity avoidance for co-bots. Based on the dynamic model with load and torque sensors, which is used to detect the external force at the end of the robot, this paper systematically analyzes the causes of singularity phenomenon in the robot motion control. The inverse solution is obtained by analytical method and numerical method, respectively. In order to ensure the smooth and safe operation in the whole workspace, it is necessary for a robot to avoid singularity. Singularity avoidance schemes are utilized for different control tasks, including point-to-point control and continuous path control. Corresponding simulation experiments are designed to verify the effectiveness of different evasion schemes, in which the advantages and disadvantages are compared and analyzed. Full article
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14 pages, 3321 KiB  
Article
Integration and Testing of a High-Torque Servo-Driven Joint and Its Electronic Controller with Application in a Prototype Upper Limb Exoskeleton
by Manuel Andrés Vélez-Guerrero, Mauro Callejas-Cuervo and Stefano Mazzoleni
Sensors 2021, 21(22), 7720; https://doi.org/10.3390/s21227720 - 20 Nov 2021
Cited by 4 | Viewed by 2633
Abstract
Mechatronic systems that allow motorized activation in robotic exoskeletons have evolved according to their specific applications and the characteristics of the actuation system, including parameters such as size, mechanical properties, efficiency, and power draw. Additionally, different control strategies and methods could be implemented [...] Read more.
Mechatronic systems that allow motorized activation in robotic exoskeletons have evolved according to their specific applications and the characteristics of the actuation system, including parameters such as size, mechanical properties, efficiency, and power draw. Additionally, different control strategies and methods could be implemented in various electronic devices to improve the performance and usability of these devices, which is desirable in any application. This paper proposes the integration and testing of a high-torque, servo-driven joint and its electronic controller, exposing its use in a robotic exoskeleton prototype as a case study. Following a brief background review, the development and implementation of the proposal are presented, allowing the control of the servo-driven joint in terms of torque, rotational velocity, and position through a straightforward, closed-loop control architecture. Additionally, the stability and performance of the servo-driven joint were assessed with and without load. In conclusion and based on the obtained results, the servo-driven joint and its control system demonstrate consistent performance under the proposed test protocol (max values: angular velocity 97 °/s, torque 33 Nm, positioning RMSE 1.46°), enabling this approach for use in various applications related to robotic exoskeletons, including human performance enhancement, rehabilitation, or support for daily living activities. Full article
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