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Time-Optimal Path Tracking for Industrial Robots: A Dynamic Model-Free Reinforcement Learning Approach
[article]
2019
arXiv
pre-print
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In pursuit of the time-optimal path tracking (TOPT) trajectory of a robot manipulator along a preset path, a beforehand identified robot dynamic model is usually used to obtain the required optimal trajectory ...
for perfect tracking. ...
Although model-based reinforcement learning algorithm does exist, most of the above-mentioned reinforcement learning algorithms for robots are model-free. ...
arXiv:1907.01348v3
fatcat:hahgs6biwbg57fk7jmtjgncili
Special Feature on Advanced Mobile Robotics
2019
Applied Sciences
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Mobile robots and their applications are involved with many research fields including electrical engineering, mechanical engineering, computer science, artificial intelligence and cognitive science [.. ...
[40] proposed a grip planning method for biped robots to produce optimal collision-free grip sequences under kinematic constraints. ...
It uses a system model with radial-basis function neural network. The control system provides high tracking accuracy as well as fast response time. Kelemen et al. ...
doi:10.3390/app9214686
fatcat:25p6a4yjxzd25anrryk5cdghii
Sensors for Robots
2024
Sensors
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Currently, robots are playing significant roles in industry [...] ...
In Contribution 1, the authors proposed a multi-path scattering model for virtual vegetation. ...
To achieve this target, this study specified the problem as a Markov decision process (MDP) and deployed a deep reinforcement learning (RL) temporal difference model-free algorithm known as the deep Q-network ...
doi:10.3390/s24061854
pmid:38544116
pmcid:PMC10975082
fatcat:h7rwfz745bgffpw7abvdhhfdly
Mobile Robot Navigation and Obstacle Avoidance Techniques: A Review
2017
International Robotics & Automation Journal
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Several techniques have been applied by the various researchers for mobile robot navigation and obstacle avoidance. ...
The applications of the autonomous mobile robot in many fields such as industry, space, defence and transportation, and other social sectors are growing day by day. ...
Real-time collision-free path planning becomes more difficult when the robot is moving in a dynamic and unstructured environment. ...
doi:10.15406/iratj.2017.02.00023
fatcat:m6viumq36zf5zbfeexua475gjy
Aerial Field Robotics
[chapter]
2022
Encyclopedia of Robotics
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2024 pre-print arXiv:2401.10837v1 fatcat:wspqn324kzg2bba42vlms2ext4
We conclude with notable contributions and discuss considerations for future research that are essential for resilience in aerial robotics. ...
Aerial field robotics research represents the domain of study that aims to equip unmanned aerial vehicles - and as it pertains to this chapter, specifically Micro Aerial Vehicles (MAVs)- with the ability ...
Provided a map, the planning architecture employs a policy for searching admissible paths that optimizes specified objectives for the robot. ...
doi:10.1007/978-3-642-41610-1_221-1
fatcat:mpvrn2v4lvhlbnjmds7vxy2ali
On the Development of Learning Control for Robotic Manipulators
2017
Robotics
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This review is able to give a general guideline for future research in learning control for robotic manipulators. ...
Learning control in robotic manipulators is mainly used to address the issue that the friction at the joints of robotic mechanisms and other uncertainties may exist in the dynamic models, which are very ...
In [28] , the authors employed the model-free feedback-assisted iterative learning control scheme for the purpose of the path tracking of a 6-DOF mechanism. ...
doi:10.3390/robotics6040023
fatcat:k2zex76mz5fk3p6jiuy5mlde54
Table of Contents
2021
2021 9th RSI International Conference on Robotics and Mechatronics (ICRoM)
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.................281 Design of an Optimized Fuzzy Controller for a 3R Non-planar Robotic Manipulator ......................287 On the effectiveness of Stable Model Predictive vs. ...
.........................................230 Multirate Adaptive Inverse Dynamics Control of 5 DOF Industrial Gryphon Robot ........................255 Design of a Reinforcement Learning based PID Controller ...
doi:10.1109/icrom54204.2021.9663492
fatcat:nchpnhiwjbhazeuq3iw4sp2mxu
A Survey for Machine Learning-Based Control of Continuum Robots
2021
Frontiers in Robotics and AI
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However, the trade-off between flexibility and controllability of soft manipulators may not be readily optimized but would be demanded for specific kinds of modeling approaches. ...
In its application of minimally invasive surgery, such a continuum concept shares the same view of robotization for conventional endoscopy/laparoscopy. ...
In the following sections, for the sake of clear expression, methods with kinematics/dynamics model denote model-based reinforcement learning; while those without such model represent model-free approaches ...
doi:10.3389/frobt.2021.730330
pmid:34692777
pmcid:PMC8527450
fatcat:p4yeo5jqajfhphzsdbiu746swa
A Review of Path-Planning Approaches for Multiple Mobile Robots
2022
Machines
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Finally, the new challenge in multi-robot path planning is proposed as fault tolerance, which is important for real-time operations. ...
This paper reviews multi-robot path-planning approaches and decision-making strategies and presents the path-planning algorithms for various types of robots, including aerial, ground, and underwater robots ...
A multi-robot path-planning algorithm for industrial robots is presented based on the first low polynomial-time algorithm on grids [122] . ...
doi:10.3390/machines10090773
fatcat:bojo6szg7jcqzkipleoxj4e3qi
Learning Robotic Assembly from CAD
[article]
2018
arXiv
pre-print
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Reinforcement learning (RL) is a promising approach for autonomously acquiring robot skills that involve contact-rich dynamics. ...
We show that our approach effectively improves over traditional control approaches for tracking the motion plan, and can solve assembly tasks that require high precision, even without accurate state estimation ...
The authors would like to thank Menglong Guo for 3D-printing the objects used in our experiments. ...
arXiv:1803.07635v2
fatcat:spdof2arh5c6xocarbyrpjvipy
Reinforcement learning based compensation methods for robot manipulators
2019
Engineering applications of artificial intelligence
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The proposed learning algorithms are evaluated on a 6-DoF industrial robotic manipulator arm to follow different kinds of reference paths, such as square or a circular path, or to track a trajectory on ...
Smart robotics will be a core feature while migrating from Industry 3.0 (i.e., mass manufacturing) to Industry 4.0 (i.e., customized or social manufacturing). ...
PD is used as a baseline for model-free, non adaptive control method, while MPC is used as a reference for model-based control framework and finally ILC is chosen as a baseline for model-free and adaptive ...
doi:10.1016/j.engappai.2018.11.006
fatcat:wdkftm23hnffvn534fmhtpt2jy
2020 Index IEEE Transactions on Robotics Vol. 36
2020
IEEE Transactions on robotics
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The Author Index contains the primary entry for each item, listed under the first author's name. ...
Costanzo, M., +, TRO Feb. 2020 157-173 Industrial robots PPCPP: A Predator-Prey-Based Approach to Adaptive Coverage Path Plan-ning. ...
De Stefano, M., +, TRO Feb. 2020 189-203 An Iterative Approach for Accurate Dynamic Model Identification of Industrial Robots. ...
doi:10.1109/tro.2021.3050417
fatcat:gzwbyhjzhbdnrdp6prpokofstu
Vision-Guided MPC for Robotic Path Following Using Learned Memory-Augmented Model
2021
Frontiers in Robotics and AI
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We formulate a combination of model predictive control with image-based path planning and real-time visual feedback, based on a learned state-space dynamic model. ...
The control of the interaction between the robot and environment, following a predefined geometric surface path with high accuracy, is a fundamental problem for contact-rich tasks such as machining, polishing ...
Under the MPC approach, the path-following task can be reformulated as a discrete-time optimal control problem (OCP) for the current time t: with the objective of minimizing a cost function J over a given ...
doi:10.3389/frobt.2021.688275
fatcat:jajsm4q3kfgkxfm4qwteoiniuq
Vision-Based Mobile Robot Controllers: A Scientific Review
2021
Turkish Journal of Computer and Mathematics Education
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Others are for military usages such as drones and the pets robots just for entertainment. ...
Today, there are different types of self-controlled robots. Some of them had critical effects on our lives like industrial and medical robots. ...
The proposed model utilizes a supervised approach for the feature extraction and reinforcement method to process and predict the output. ...
doi:10.17762/turcomat.v12i6.2695
fatcat:hxdsdt2kl5hs3eswac4ckeuv6i
2021 Index IEEE Robotics and Automation Letters Vol. 6
2021
IEEE Robotics and Automation Letters
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The Author Index contains the primary entry for each item, listed under the first author's name. ...
., +, LRA July 2021 5324-5331 Dual-Objective Collision-Free Path Optimization of Arc Welding Robot. ...
., +, LRA Oct. 2021 7145-7152 Arc welding Dual-Objective Collision-Free Path Optimization of Arc Welding Robot. ...
doi:10.1109/lra.2021.3119726
fatcat:lsnerdofvveqhlv7xx7gati2xu
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