Topical Collection "Advances in Automation and Robotics"

A topical collection in Applied Sciences (ISSN 2076-3417). This collection belongs to the section "Robotics and Automation".

Editors

Prof. Dr. Manuel Armada
E-Mail Website
Collection Editor
Centre for Automation and Robotics (CAR) (CSIC-UPM), Arganda del Rey, Madrid, Spain
Interests: climbing and walking robots; bi-manual robots; medical applications; computer vision; deep learning; big data; automation; control theory and robotic applications: precision agriculture, security and forensics
Dr. Roemi Fernandez
E-Mail Website1 Website2
Collection Editor
CSIC-UPM - Centro de Automatica y Robotica (CAR), Madrid, Spain
Interests: field and service robotic systems; intelligent robotics; multisensory systems; nonlinear actuators and nonlinear controllers

Topical Collection Information

Dear Colleagues,

Despite the great progress made, automation and robotics are still far from reaching their maximum potential. The unstoppable rise of digitalization and automation will redefine manufacturing processes within the framework of Industry 4.0, improving efficiency and competitiveness. In the near future, it is also expected that innovative robotic systems will be able to confront the most challenging fields of application, providing solutions that contribute to improving the quality of life of human beings. However, a great research effort is still required, not only to develop faster, more intelligent, and more autonomous robots, but also to endow these systems with new cognitive skills and with the ability to collaborate, learn, and adapt to complex changing environments and tasks.

Therefore, the objective of this Special Issue is to compile recent advances in robotics and automation. The topics of interest include but are not limited to:

  • Modeling, identification, and control of robotic systems;
  • Intelligent robotics, mechatronics, and biomimetics;
  • Industrial and collaborative robots;
  • Field and service robots;
  • Perception for robotics and automation;
  • Agile locomotion and dexterous manipulation;
  • AI in robotics and automation;
  • New applications for robotics and automation.

Original papers and survey papers are solicited for the Special Issue, covering research results as well as case studies and applications in related areas of interest.

Please do not hesitate to contact us if you have any doubts regarding your submission.

Best regards,

Dr. Manuel A. Armada
Dr. Roemi Fernandez
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the collection website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2000 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

  • automation
  • intelligent robotics
  • collaborative robots
  • perception
  • agile locomotion
  • dexterous manipulation

Published Papers (24 papers)

2021

Jump to: 2020, 2019

Article
Valkyrie—Design and Development of Gaits for Quadruped Robot Using Particle Swarm Optimization
Appl. Sci. 2021, 11(16), 7458; https://doi.org/10.3390/app11167458 - 13 Aug 2021
Viewed by 375
Abstract
Over the past decades, developments and scientific breakthroughs in the field of robotics have shown the replacement of wheeled robots with legged robots, which are often inspired by the biological characteristics of legged animals. Many industries and urban-based applications promote quadruped robots because [...] Read more.
Over the past decades, developments and scientific breakthroughs in the field of robotics have shown the replacement of wheeled robots with legged robots, which are often inspired by the biological characteristics of legged animals. Many industries and urban-based applications promote quadruped robots because of their dexterous ability to efficiently handle multiple tasks in the working environment. Motivated from the recent works in the field of quadruped robots, this research aims to develop and investigate gaits for a 2 DoF mammal-inspired quadruped robot that incorporates 4 hip and 4 knee servo motors as its locomotion element. Forward and inverse kinematic techniques are used to determine the joint angle required for the locomotion and stability calculation are presented to determine the center of mass/center of gravity of the robot. Three types of gaits such as walk, trot, and pace are developed while keeping the center of mass inside the support polygon using a closed-loop control system. To minimize errors and improve the performance of the robot due to its non-linearity, a meta-heuristic algorithm has been developed and addressed in this work. The fitness function is derived based on the Euclidean distance between the target and robot’s current position and kinematic equations are used to obtain the relation between joints and coordinates. Based on the literature, particle swarm optimization (PSO) was found to be a promising algorithm for this problem and is developed using Python’s ‘Pyswarms’ package. Experimental studies are carried out quantitatively to determine the convergence characteristics of the control algorithm and to investigate the distance traveled by the robot for different target positions and gaits. Comparison between experimental and theoretical results prove the efficiency of the proposed algorithm and stability of the robot during various gait movements. Full article
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Article
Soft Gripper with EGaIn Soft Sensor for Detecting Grasp Status
Appl. Sci. 2021, 11(15), 6957; https://doi.org/10.3390/app11156957 - 28 Jul 2021
Viewed by 349
Abstract
With the Fourth Industrial Revolution, many factories aim for efficient mass production, and robots are being used to reduce human workloads. In recent years, the field of gripper robots with a soft structure that can grip and move objects without damaging them has [...] Read more.
With the Fourth Industrial Revolution, many factories aim for efficient mass production, and robots are being used to reduce human workloads. In recent years, the field of gripper robots with a soft structure that can grip and move objects without damaging them has attracted considerable attention. This paper proposes a variable-stiffness soft gripper, based on previous designs, with an added silicone coating for increased friction and an EGaIn soft sensor for monitoring grip forces. The variable-stiffness structure used in this study was constructed by connecting soft structures to rigid structures and using tendons fixed to the rigid structures. Furthermore, a more responsive EGaIn soft sensor compared to existing sensors was designed by adding bumps to the path traced by the alloy. After selecting the appropriate fingertip shape, changes in the output of the EGaIn soft sensor corresponding to the object held by the soft gripper were observed, confirming that the strength of the device could be changed according to the intended purpose. Full article
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Article
Design and Implementation of an Autonomous Charging Station for Agricultural Electrical Vehicles
Appl. Sci. 2021, 11(13), 6168; https://doi.org/10.3390/app11136168 - 02 Jul 2021
Viewed by 470
Abstract
One of the goals in adopting more sustainable agricultural practices is to reduce green-house-gas emissions from current practices by replacing fossil-fuel-based heavy machinery with lighter, electrical ones. In a not-so-distant scenario where a single farmer owns a fleet of small electrical tractors/robots that [...] Read more.
One of the goals in adopting more sustainable agricultural practices is to reduce green-house-gas emissions from current practices by replacing fossil-fuel-based heavy machinery with lighter, electrical ones. In a not-so-distant scenario where a single farmer owns a fleet of small electrical tractors/robots that can operate in an autonomous/semi-autonomous manner, this will bring along some logistic challenges. It will be highly impractical that the farmer follows each time a given vehicle moves to the charging point to manually charge it. We present in this paper the design and implementation of an autonomous charging station to be used for that purpose. The charging station is a combination of a holonomic mobile platform and a collaborative robotic arm. Vision-based navigation and detection are used in order to plug the power cable from the wall-plug to the vehicle and back to the wall-plug again when the vehicle has recharged its batteries or reached the required level to pursue its tasks in the field. A decision-tree-based scheme is used in order to define the necessary pick, navigate, and plug sequences to fulfill the charging task. Communication between the autonomous charging station and the vehicle is established in order to make the whole process completely autonomous without any manual intervention. We present in this paper the charging station, the docking mechanism, communication scheme, and the deployed algorithms to achieve the autonomous charging process for agricultural electrical vehicles. We also present real experiments performed using the developed platform on an electrical robot-tractor. Full article
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Article
A Practical Approach for Picking Items in an Online Shopping Warehouse
Appl. Sci. 2021, 11(13), 5805; https://doi.org/10.3390/app11135805 - 23 Jun 2021
Viewed by 336
Abstract
Commercially viable automated picking in unstructured environments by a robot arm remains a difficult challenge. The problem of robot grasp planning has long been around but the existing solutions tend to be limited when it comes to deploy them in open-ended realistic scenarios. [...] Read more.
Commercially viable automated picking in unstructured environments by a robot arm remains a difficult challenge. The problem of robot grasp planning has long been around but the existing solutions tend to be limited when it comes to deploy them in open-ended realistic scenarios. Practical picking systems are called for that can handle the different properties of the objects to be manipulated, as well as the problems arising from occlusions and constrained accessibility. This paper presents a practical solution to the problem of robot picking in an online shopping warehouse by means of a novel approach that integrates a carefully selected method with a new strategy, the centroid normal approach (CNA), on a cost-effective dual-arm robotic system with two grippers specifically designed for this purpose: a two-finger gripper and a vacuum gripper. Objects identified in the scene point cloud are matched to the grasping techniques and grippers to maximize success. Extensive experimentation provides clues as to what are the reasons for success and failure. We chose as benchmark the scenario proposed by the 2017 Amazon Robotics Challenge, since it represents a realistic description of a retail shopping warehouse case; it includes many challenging constraints, such as a wide variety of different product items with a diversity of properties, which are also presented with restricted visibility and accessibility. Full article
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Article
Consensus of Multi-Agent Systems with Unbounded Time-Varying Delays
Appl. Sci. 2021, 11(11), 4944; https://doi.org/10.3390/app11114944 - 27 May 2021
Viewed by 806
Abstract
In multi-agent systems with increasing communication distances, the communication delay is time-varying and unbounded. In this paper, we describe the multi-agent system with increasing communication distances as the discrete-time system with non-distributed unbounded time-varying delays and study the consensus problem of the system [...] Read more.
In multi-agent systems with increasing communication distances, the communication delay is time-varying and unbounded. In this paper, we describe the multi-agent system with increasing communication distances as the discrete-time system with non-distributed unbounded time-varying delays and study the consensus problem of the system via the distributed control. This paper uses a time-delay system to model the discrete-time system, and the maximum delay in the time-delay system tends to infinity as time goes on. Furthermore, caused by this property, most of convergence analysis methods for bounded time-delay systems are ineffective. Hence, for any finite integer k>0, the finite-dimensional augmented model of the time-delay system is built in the interval [0,k] to study the system state. Under the weaker topological assumption that the topology containing a spanning tree, the system is proved to achieve a consensus if the growth rate of the maximum delay satisfies some mild constraints, which also are constraints on the growth rate of the maximum communication distance between agents. Furthermore, we characterize that the rate of the system achieving a consensus and the growth rate of the maximum delay are negatively correlated. In other words, the rate of the system achieving a consensus and the growth rate of the maximum communication distance between agents are negatively correlated. Full article
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Article
A Mobile Service Robot Global Path Planning Method Based on Ant Colony Optimization and Fuzzy Control
Appl. Sci. 2021, 11(8), 3605; https://doi.org/10.3390/app11083605 - 16 Apr 2021
Cited by 1 | Viewed by 499
Abstract
A global path planning method is proposed based on improved ant colony optimization according to the slow convergence speed in mobile service robot path planning. The distribution of initial pheromone is determined by the critical obstacle influence factor. The influence factor is introduced [...] Read more.
A global path planning method is proposed based on improved ant colony optimization according to the slow convergence speed in mobile service robot path planning. The distribution of initial pheromone is determined by the critical obstacle influence factor. The influence factor is introduced into the heuristic information to improve the convergence speed of the algorithm at an early stage. A new pheromone update rule is presented using fuzzy control to change the value of pheromone heuristic factor and expectation heuristic factor, adjusting the evaporation rate in stages. The method achieves fast convergence and guarantees global search capability. Finally, the simulation results show that the improved algorithm not only shortens the running time of global path planning, but also has a higher probability of obtaining a global optimal solution. The convergence speed of the algorithm is better than the traditional ant colony algorithm. Full article
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Review
Object Detection, Distributed Cloud Computing and Parallelization Techniques for Autonomous Driving Systems
Appl. Sci. 2021, 11(7), 2925; https://doi.org/10.3390/app11072925 - 25 Mar 2021
Viewed by 987
Abstract
Autonomous vehicles are increasingly becoming a necessary trend towards building the smart cities of the future. Numerous proposals have been presented in recent years to tackle particular aspects of the working pipeline towards creating a functional end-to-end system, such as object detection, tracking, [...] Read more.
Autonomous vehicles are increasingly becoming a necessary trend towards building the smart cities of the future. Numerous proposals have been presented in recent years to tackle particular aspects of the working pipeline towards creating a functional end-to-end system, such as object detection, tracking, path planning, sentiment or intent detection, amongst others. Nevertheless, few efforts have been made to systematically compile all of these systems into a single proposal that also considers the real challenges these systems will have on the road, such as real-time computation, hardware capabilities, etc. This paper reviews the latest techniques towards creating our own end-to-end autonomous vehicle system, considering the state-of-the-art methods on object detection, and the possible incorporation of distributed systems and parallelization to deploy these methods. Our findings show that while techniques such as convolutional neural networks, recurrent neural networks, and long short-term memory can effectively handle the initial detection and path planning tasks, more efforts are required to implement cloud computing to reduce the computational time that these methods demand. Additionally, we have mapped different strategies to handle the parallelization task, both within and between the networks. Full article
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Article
State Estimation of Over-Sensored Systems Applied to a Low-Cost Robotic Manipulator
Appl. Sci. 2021, 11(6), 2519; https://doi.org/10.3390/app11062519 - 11 Mar 2021
Viewed by 451
Abstract
There is an increasing demand for robotic manipulators to perform more complex and versatile tasks. In order to fulfill this need, expeditious calibration and estimation techniques are required as a first step for the correct usage of the manipulator. This article aims at [...] Read more.
There is an increasing demand for robotic manipulators to perform more complex and versatile tasks. In order to fulfill this need, expeditious calibration and estimation techniques are required as a first step for the correct usage of the manipulator. This article aims at finding a subset of these algorithms that could be used in a generic manipulator and should allow for its prompt use. Two models for the representation of the pose of the manipulator are described and used in the state estimation problem. The results of the implementation are tested, and some performance metrics are obtained. Full article
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Article
Efficient Detection of Robot Kidnapping in Range Finder-Based Indoor Localization Using Quasi-Standardized 2D Dynamic Time Warping
Appl. Sci. 2021, 11(4), 1580; https://doi.org/10.3390/app11041580 - 09 Feb 2021
Viewed by 574
Abstract
This paper proposes an augmented online approach to detect kidnapping events within range-finder-based indoor localization. The method is specifically designed for an Internet of Things (IoT)-Aided Robotics Platform that enables the system to detect kidnapping across all time instances of an indoor mobile [...] Read more.
This paper proposes an augmented online approach to detect kidnapping events within range-finder-based indoor localization. The method is specifically designed for an Internet of Things (IoT)-Aided Robotics Platform that enables the system to detect kidnapping across all time instances of an indoor mobile robotic operation with high accuracy and maintain a high accuracy in the face of relocalization failures. The approach is based on similarity degree of geometry shape of the environment obtained from range scan data between two consecutive time instances. The proposed approach named Quasi-Standardized Two-Dimensional Dynamic Time Warping (QS-2DDTW) is based on the Multidimensional Dynamic Time Warping (MD-DTW) with homogeneity variance test imbued in it. A series of simulations are preformed against maximum current weight, measurement entropy, and the four metrics in metric based detector. The result shows that the proposed method yields high performance in terms of its ability to distinguish kidnapping condition from normal condition and that it has low dependency towards relocalization process, thus ensures the accuracy of detection is not disturbed by relocalization. Full article
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Article
Deliberative and Conceptual Inference in Service Robots
Appl. Sci. 2021, 11(4), 1523; https://doi.org/10.3390/app11041523 - 08 Feb 2021
Viewed by 595
Abstract
Service robots need to reason to support people in daily life situations. Reasoning is an expensive resource that should be used on demand whenever the expectations of the robot do not match the situation of the world and the execution of the task [...] Read more.
Service robots need to reason to support people in daily life situations. Reasoning is an expensive resource that should be used on demand whenever the expectations of the robot do not match the situation of the world and the execution of the task is broken down; in such scenarios, the robot must perform the common sense daily life inference cycle consisting on diagnosing what happened, deciding what to do about it, and inducing and executing a plan, recurring in such behavior until the service task can be resumed. Here, we examine two strategies to implement this cycle: (1) a pipe-line strategy involving abduction, decision-making, and planning, which we call deliberative inference and (2) the use of the knowledge and preferences stored in the robot’s knowledge-base, which we call conceptual inference. The former involves an explicit definition of a problem-space that is explored through heuristic search, and the latter is based on conceptual knowledge, including the human user preferences, and its representation requires a non-monotonic knowledge-based system. We compare the strengths and limitations of both approaches. We also describe a service robot conceptual model and architecture capable of supporting the daily life inference cycle during the execution of a robotics service task. The model is centered in the declarative specification and interpretation of robot’s communication and task structure. We also show the implementation of this framework in the fully autonomous robot Golem-III. The framework is illustrated with two demonstration scenarios. Full article
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2020

Jump to: 2021, 2019

Article
Calligraphy Brush Trajectory Control of by a Robotic Arm
Appl. Sci. 2020, 10(23), 8694; https://doi.org/10.3390/app10238694 - 04 Dec 2020
Viewed by 455
Abstract
This study proposed a calligraphy brush trajectory model for the behavior of brush movements and provided the three-dimensional handle coordinates for a robotic arm to write calligraphy. This study dealt with basic footprints and bent lines of calligraphy and proceeded as follows. The [...] Read more.
This study proposed a calligraphy brush trajectory model for the behavior of brush movements and provided the three-dimensional handle coordinates for a robotic arm to write calligraphy. This study dealt with basic footprints and bent lines of calligraphy and proceeded as follows. The shape of brush footprints on paper was measured, which provided the positions of the brush relative to its handle. These brush footprints were scanned and corrected for skew using the Direct Linear Transformation. The outer frame of each basic footprint was characterized using Bézier curves. Bent lines were drawn to derive the brush trajectory model, and it was used to derive the relationship between the trajectories of the brush and handle. By characterizing the changes in the footprints with handle displacement, we obtained the relationship between the handle coordinates and the position and shape of the brush footprints. The written characters were evaluated based on their size, position, and stroke balance, with a maximum score of 100 in each category. The average score of the “Yong” character written using our brush trajectory model was approximately 94 points; when the handle coordinates were fixed to the center of each footprint, the average score was only 88 points. Full article
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Article
Novel Human-in-the-Loop (HIL) Simulation Method to Study Synthetic Agents and Standardize Human–Machine Teams (HMT)
Appl. Sci. 2020, 10(23), 8390; https://doi.org/10.3390/app10238390 - 25 Nov 2020
Viewed by 740
Abstract
This work presents a multi-year study conducted at the University of Toledo, aimed at improving human–machine teaming (HMT) methods and technologies. With the advent of artificial intelligence (AI) in 21st-century machines, collaboration between humans and machines has become highly complicated for real-time applications. [...] Read more.
This work presents a multi-year study conducted at the University of Toledo, aimed at improving human–machine teaming (HMT) methods and technologies. With the advent of artificial intelligence (AI) in 21st-century machines, collaboration between humans and machines has become highly complicated for real-time applications. The penetration of intelligent and synthetic assistants (IA/SA) in virtually every field has opened up a path to the area of HMT. When it comes to crucial tasks such as patient treatment/care, industrial production, and defense, the use of non-standardized HMT technologies may pose a risk to human lives and cost billions of taxpayer dollars. A thorough literature survey revealed that there are not many established standards or benchmarks for HMT. In this paper, we propose a method to design an HMT based on a generalized architecture. This design includes the development of an intelligent collaborative system and the human team. Followed by the identification of processes and metrics to test and validate the proposed model, we present a novel human-in-the-loop (HIL) simulation method. The effectiveness of this method is demonstrated using two controlled HMT scenarios: Emergency care provider (ECP) training and patient treatment by an experienced medic. Both scenarios include humans processing visual data and performing actions that represent real-world applications while responding to a Voice-Based Synthetic Assistant (VBSA) as a collaborator that keeps track of actions. The impact of various machines, humans, and HMT parameters is presented from the perspective of performance, rules, roles, and operational limitations. The proposed HIL method was found to assist in standardization studies in the pursuit of HMT benchmarking for critical applications. Finally, we present guidelines for designing and benchmarking HMTs based on the case studies’ results analysis. Full article
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Article
Compact Spatial Pyramid Pooling Deep Convolutional Neural Network Based Hand Gestures Decoder
Appl. Sci. 2020, 10(21), 7898; https://doi.org/10.3390/app10217898 - 07 Nov 2020
Cited by 2 | Viewed by 607
Abstract
Current deep learning convolutional neural network (DCNN) -based hand gesture detectors with acute precision demand incredibly high-performance computing power. Although DCNN-based detectors are capable of accurate classification, the sheer computing power needed for this form of classification makes it very difficult to run [...] Read more.
Current deep learning convolutional neural network (DCNN) -based hand gesture detectors with acute precision demand incredibly high-performance computing power. Although DCNN-based detectors are capable of accurate classification, the sheer computing power needed for this form of classification makes it very difficult to run with lower computational power in remote environments. Moreover, classical DCNN architectures have a fixed number of input dimensions, which forces preprocessing, thus making it impractical for real-world applications. In this research, a practical DCNN with an optimized architecture is proposed with DCNN filter/node pruning, and spatial pyramid pooling (SPP) is introduced in order to make the model input dimension-invariant. This compact SPP-DCNN module uses 65% fewer parameters than traditional classifiers and operates almost 3× faster than classical models. Moreover, the new improved proposed algorithm, which decodes gestures or sign language finger-spelling from videos, gave a benchmark highest accuracy with the fastest processing speed. This proposed method paves the way for various practical and applied hand gesture input-based human-computer interaction (HCI) applications. Full article
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Article
A Vision-Based Two-Stage Framework for Inferring Physical Properties of the Terrain
Appl. Sci. 2020, 10(18), 6473; https://doi.org/10.3390/app10186473 - 17 Sep 2020
Cited by 2 | Viewed by 688
Abstract
The friction and stiffness properties of the terrain are very important pieces of information for mobile robots in motion control, dynamics parameter adjustment, trajectory planning, etc. Inferring the friction and stiffness properties in advance can improve the safety, adaptability and reliability, and reduce [...] Read more.
The friction and stiffness properties of the terrain are very important pieces of information for mobile robots in motion control, dynamics parameter adjustment, trajectory planning, etc. Inferring the friction and stiffness properties in advance can improve the safety, adaptability and reliability, and reduce the energy consumption of the robot. This paper proposes a vision-based two-stage framework for pre-estimating physical properties of the terrain. We established a field terrain image dataset with weak annotations. A semantic segmentation network that can segment terrains at the pixel level was designed. Given that the same terrain also has different physical properties, we designed two kinds of image features, and we use a decision-making model to realize the mapping from terrain to physical properties. We trained and tested the network comprehensively, and experimented with the complete framework for estimating physical properties. The experimental results show that our framework has good performance. Full article
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Project Report
Recent Developments Regarding Painting Robots for Research in Automatic Painting, Artificial Creativity, and Machine Learning
Appl. Sci. 2020, 10(10), 3396; https://doi.org/10.3390/app10103396 - 14 May 2020
Cited by 1 | Viewed by 1130
Abstract
E-David (Electronic Drawing Apparatus for Vivid Image Display) is a system for controlling a variety of painting machines in order to create robotic paintings. This article summarizes the hardware set-up used for painting, along with recent developments, lessons learned from past painting machines, [...] Read more.
E-David (Electronic Drawing Apparatus for Vivid Image Display) is a system for controlling a variety of painting machines in order to create robotic paintings. This article summarizes the hardware set-up used for painting, along with recent developments, lessons learned from past painting machines, as well as plans for new approaches. We want to apply e-David as a platform for research towards improving automatic painting and to explore machine creativity. We present different painting machines, from small low-cost plotters to large industrial robots, and discuss the benefits and limitations of each type of platform and present their applicability to different tasks within the domain of robotic painting and artificial creativity research. A unified control interface with a scripting language allows users a simplified usage of different e-David-like machines. Furthermore, we present our system for automated stroke experimentation and recording, which is an advance towards allowing the machine to autonomously learn about brush dynamics. Finally, we also show how e-David can be used by artists “in the field” for different exhibitions. Full article
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Article
Synthesis of the Inverse Kinematic Model of Non-Redundant Open-Chain Robotic Systems Using Groebner Basis Theory
Appl. Sci. 2020, 10(8), 2781; https://doi.org/10.3390/app10082781 - 17 Apr 2020
Cited by 2 | Viewed by 965
Abstract
One of the most important elements of a robot’s control system is its Inverse Kinematic Model (IKM), which calculates the position and velocity references required by the robot’s actuators to follow a trajectory. The methods that are commonly used to synthesize the IKM [...] Read more.
One of the most important elements of a robot’s control system is its Inverse Kinematic Model (IKM), which calculates the position and velocity references required by the robot’s actuators to follow a trajectory. The methods that are commonly used to synthesize the IKM of open-chain robotic systems strongly depend on the geometry of the analyzed robot. Those methods are not systematic procedures that could be applied equally in all possible cases. This project presents the development of a systematic procedure to synthesize the IKM of non-redundant open-chain robotic systems using Groebner Basis theory, which does not depend on the geometry of the robot’s structure. The inputs to the developed procedure are the robot’s Denavit–Hartenberg parameters, while the output is the IKM, ready to be used in the robot’s control system or in a simulation of its behavior. The Groebner Basis calculation is done in a two-step process, first computing a basis with Faugère’s F4 algorithm and a grevlex monomial order, and later changing the basis with the FGLM algorithm to the desired lexicographic order. This procedure’s performance was proved calculating the IKM of a PUMA manipulator and a walking hexapod robot. The errors in the computed references of both IKMs were absolutely negligible in their corresponding workspaces, and their computation times were comparable to those required by the kinematic models calculated by traditional methods. The developed procedure can be applied to all Cartesian robotic systems, SCARA robots, all the non-redundant robotic manipulators that satisfy the in-line wrist condition, and any non-redundant open-chain robot whose IKM should only solve the positioning problem, such as multi-legged walking robots. Full article
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Article
Control Methods Comparison for the Real Quadrotor on an Innovative Test Stand
Appl. Sci. 2020, 10(6), 2064; https://doi.org/10.3390/app10062064 - 18 Mar 2020
Cited by 3 | Viewed by 763
Abstract
This article is a continuation of our previously published work that presented a comparison of nine attitude quaternion-based controllers of the quadrotor in simulation environment. In this article, the best three controllers were implemented into the real quadrotor. Namely proportional derivative (PD), linear [...] Read more.
This article is a continuation of our previously published work that presented a comparison of nine attitude quaternion-based controllers of the quadrotor in simulation environment. In this article, the best three controllers were implemented into the real quadrotor. Namely proportional derivative (PD), linear quadratic regulator (LQR) and backstepping quaternion-based control techniques were evaluated. As a suitable test stand was not available on the basis of literature analysis, the article also outlines the requirements and the development of a new innovative test stand. In order to provide a comprehensive overview, the hardware and software that was used is also presented in the article. The main contribution of this article is a performance comparison of the controllers, which was based on absolute quaternion (positioning) error and energy consumption. Full article
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Article
Motion Planning of Robot Manipulators for a Smoother Path Using a Twin Delayed Deep Deterministic Policy Gradient with Hindsight Experience Replay
Appl. Sci. 2020, 10(2), 575; https://doi.org/10.3390/app10020575 - 13 Jan 2020
Cited by 11 | Viewed by 1596
Abstract
In order to enhance performance of robot systems in the manufacturing industry, it is essential to develop motion and task planning algorithms. Especially, it is important for the motion plan to be generated automatically in order to deal with various working environments. Although [...] Read more.
In order to enhance performance of robot systems in the manufacturing industry, it is essential to develop motion and task planning algorithms. Especially, it is important for the motion plan to be generated automatically in order to deal with various working environments. Although PRM (Probabilistic Roadmap) provides feasible paths when the starting and goal positions of a robot manipulator are given, the path might not be smooth enough, which can lead to inefficient performance of the robot system. This paper proposes a motion planning algorithm for robot manipulators using a twin delayed deep deterministic policy gradient (TD3) which is a reinforcement learning algorithm tailored to MDP with continuous action. Besides, hindsight experience replay (HER) is employed in the TD3 to enhance sample efficiency. Since path planning for a robot manipulator is an MDP (Markov Decision Process) with sparse reward and HER can deal with such a problem, this paper proposes a motion planning algorithm using TD3 with HER. The proposed algorithm is applied to 2-DOF and 3-DOF manipulators and it is shown that the designed paths are smoother and shorter than those designed by PRM. Full article
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Article
Semantic Information for Robot Navigation: A Survey
Appl. Sci. 2020, 10(2), 497; https://doi.org/10.3390/app10020497 - 09 Jan 2020
Cited by 9 | Viewed by 1924
Abstract
There is a growing trend in robotics for implementing behavioural mechanisms based on human psychology, such as the processes associated with thinking. Semantic knowledge has opened new paths in robot navigation, allowing a higher level of abstraction in the representation of information. In [...] Read more.
There is a growing trend in robotics for implementing behavioural mechanisms based on human psychology, such as the processes associated with thinking. Semantic knowledge has opened new paths in robot navigation, allowing a higher level of abstraction in the representation of information. In contrast with the early years, when navigation relied on geometric navigators that interpreted the environment as a series of accessible areas or later developments that led to the use of graph theory, semantic information has moved robot navigation one step further. This work presents a survey on the concepts, methodologies and techniques that allow including semantic information in robot navigation systems. The techniques involved have to deal with a range of tasks from modelling the environment and building a semantic map, to including methods to learn new concepts and the representation of the knowledge acquired, in many cases through interaction with users. As understanding the environment is essential to achieve high-level navigation, this paper reviews techniques for acquisition of semantic information, paying attention to the two main groups: human-assisted and autonomous techniques. Some state-of-the-art semantic knowledge representations are also studied, including ontologies, cognitive maps and semantic maps. All of this leads to a recent concept, semantic navigation, which integrates the previous topics to generate high-level navigation systems able to deal with real-world complex situations. Full article
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2019

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Article
Primitive Shape Fitting in Point Clouds Using the Bees Algorithm
Appl. Sci. 2019, 9(23), 5198; https://doi.org/10.3390/app9235198 - 29 Nov 2019
Cited by 2 | Viewed by 906
Abstract
In this study the problem of fitting shape primitives to point cloud scenes was tackled as a parameter optimisation procedure, and solved using the popular bees algorithm. Tested on three sets of clean and differently blurred point cloud models, the bees algorithm obtained [...] Read more.
In this study the problem of fitting shape primitives to point cloud scenes was tackled as a parameter optimisation procedure, and solved using the popular bees algorithm. Tested on three sets of clean and differently blurred point cloud models, the bees algorithm obtained performances comparable to those obtained using the state-of-the-art random sample consensus (RANSAC) method, and superior to those obtained by an evolutionary algorithm. Shape fitting times were compatible with real-time application. The main advantage of the bees algorithm over standard methods is that it doesn’t rely on ad hoc assumptions about the nature of the point cloud model like RANSAC approximation tolerance. Full article
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Review
Learning and Comfort in Human–Robot Interaction: A Review
Appl. Sci. 2019, 9(23), 5152; https://doi.org/10.3390/app9235152 - 28 Nov 2019
Cited by 10 | Viewed by 1248
Abstract
Collaborative robots provide prospective and great solutions to human–robot cooperative tasks. In this paper, we present a comprehensive review for two significant topics in human–robot interaction: robots learning from demonstrations and human comfort. The collaboration quality between the human and the robot has [...] Read more.
Collaborative robots provide prospective and great solutions to human–robot cooperative tasks. In this paper, we present a comprehensive review for two significant topics in human–robot interaction: robots learning from demonstrations and human comfort. The collaboration quality between the human and the robot has been improved largely by taking advantage of robots learning from demonstrations. Human teaching and robot learning approaches with their corresponding applications are investigated in this review. We also discuss several important issues that need to be paid attention to and addressed in the human–robot teaching–learning process. After that, the factors that may affect human comfort in human–robot interaction are described and discussed. Moreover, the measures utilized to improve human acceptance of robots and human comfort in human–robot interaction are also presented and discussed. Full article
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Article
Pull-Based Distributed Event-Triggered Circle Formation Control for Multi-Agent Systems with Directed Topologies
Appl. Sci. 2019, 9(23), 4995; https://doi.org/10.3390/app9234995 - 20 Nov 2019
Cited by 6 | Viewed by 705
Abstract
This paper investigates a circle formation control problem for multi-agent systems with directed topologies via pull-based distributed event-triggered control principles. Firstly, for scenarios of continuous communication, a pull-based distributed event-triggered principle is proposed. It is proved that if the communication topology is irreducible [...] Read more.
This paper investigates a circle formation control problem for multi-agent systems with directed topologies via pull-based distributed event-triggered control principles. Firstly, for scenarios of continuous communication, a pull-based distributed event-triggered principle is proposed. It is proved that if the communication topology is irreducible and has a directed spanning tree, the event-triggered coupling continuous communication can lead multiple agents to form a desired circle formation. Then, the results are extended to discontinuous communication scenarios, where all the agents use a model of their neighborhoods to generate self-triggered instants without monitoring continuously, update the local controller here, and if necessary, local broadcast information based on the adopted control inputs to neighboring agents. In addition, Zeno behavior can be excluded during the whole process. Finally, numerical simulation results are given to demonstrate the effectiveness of the proposed circle formation control methods. Full article
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Article
POU-SLAM: Scan-to-Model Matching Based on 3D Voxels
Appl. Sci. 2019, 9(19), 4147; https://doi.org/10.3390/app9194147 - 03 Oct 2019
Cited by 1 | Viewed by 1003
Abstract
Purpose: Localization and mapping with LiDAR data is a fundamental building block for autonomous vehicles. Though LiDAR point clouds can often encode the scene depth more accurate and steadier compared with visual information, laser-based Simultaneous Localization And Mapping (SLAM) remains challenging as the [...] Read more.
Purpose: Localization and mapping with LiDAR data is a fundamental building block for autonomous vehicles. Though LiDAR point clouds can often encode the scene depth more accurate and steadier compared with visual information, laser-based Simultaneous Localization And Mapping (SLAM) remains challenging as the data is usually sparse, density variable and less discriminative. The purpose of this paper is to propose an accurate and reliable laser-based SLAM solution. Design/methodology/approach: The method starts with constructing voxel grids based on the 3D input point cloud. These voxels are then classified into three types to indicate different physical objects according to the spatial distribution of the points contained in each voxel. During the mapping process, a global environment model with Partition of Unity (POU) implicit surface is maintained and the voxels are merged into the model from stage to stage, which is implemented by Levenberg–Marquardt algorithm. Findings: We propose a laser-based SLAM method. The method uses POU implicit surface representation to build the model and is evaluated on the KITTI odometry benchmark without loop closure. Our method achieves around 30% translational estimation precision improvement with acceptable sacrifice of efficiency compared to LOAM. Overall, our method uses a more complex and accurate surface representation than LOAM to increase the mapping accuracy at the expense of computational efficiency. Experimental results indicate that the method achieves accuracy comparable to the state-of-the-art methods. Originality/value: We propose a novel, low-drift SLAM method that falls into a scan-to-model matching paradigm. The method, which operates on point clouds obtained from Velodyne HDL64, is of value to researchers developing SLAM systems for autonomous vehicles. Full article
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Article
A Novel Hybrid Fuzzy Grey TOPSIS Method: Supplier Evaluation of a Collaborative Manufacturing Enterprise
Appl. Sci. 2019, 9(18), 3770; https://doi.org/10.3390/app9183770 - 09 Sep 2019
Cited by 24 | Viewed by 1067
Abstract
Recently, there is of significant interest in developing multi-criteria decision making (MCDM) techniques with large applications for real-life problems. Making a reasonable and accurate decision on MCDM problems can help develop enterprises better. The existing MCDM methods, such as the grey comprehensive evaluation [...] Read more.
Recently, there is of significant interest in developing multi-criteria decision making (MCDM) techniques with large applications for real-life problems. Making a reasonable and accurate decision on MCDM problems can help develop enterprises better. The existing MCDM methods, such as the grey comprehensive evaluation (GCE) method and the technique for order preference by similarity to an ideal solution (TOPSIS), have their one-sidedness and shortcomings. They neither consider the difference of shape and the distance of the evaluation sequence of alternatives simultaneously nor deal with the interaction that universally exists among criteria. Furthermore, some enterprises cannot consult the best professional expert, which leads to inappropriate decisions. These reasons motivate us to contribute a novel hybrid MCDM technique called the grey fuzzy TOPSIS (FGT). It applies fuzzy measures and fuzzy integral to express and integrate the interaction among criteria, respectively. Fuzzy numbers are employed to help the experts to make more reasonable and accurate evaluations. The GCE method and the TOPSIS are combined to improve their one-sidedness. A case study of supplier evaluation of a collaborative manufacturing enterprise verifies the effectiveness of the hybrid method. The evaluation result of different methods shows that the proposed approach overcomes the shortcomings of GCE and TOPSIS. The proposed hybrid decision-making model provides a more accurate and reliable method for evaluating the fuzzy system MCDM problems with interaction criteria. Full article
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