Obstacle Avoidance for Kinematically Redundant Manipulators Based on Recurrent Neural Networks

Intelligent Robotics and Applications - Lecture Notes in Computer Science ◽

10.1007/978-3-540-88513-9_2 ◽

2008 ◽

pp. 10-13 ◽

Cited By ~ 1

Author(s):

Jun Wang

Keyword(s):

Neural Networks ◽

Obstacle Avoidance ◽

Recurrent Neural Networks ◽

Redundant Manipulators

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Motion planning with obstacle avoidance for kinematically redundant manipulators based on two recurrent neural networks

2009 IEEE International Conference on Systems, Man and Cybernetics ◽

10.1109/icsmc.2009.5346561 ◽

2009 ◽

Cited By ~ 7

Author(s):

Xiaolin Hu ◽

Jun Wang ◽

Bo Zhang

Keyword(s):

Neural Networks ◽

Motion Planning ◽

Obstacle Avoidance ◽

Recurrent Neural Networks ◽

Redundant Manipulators

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Deep Recurrent Neural Networks Based Obstacle Avoidance Control for Redundant Manipulators

Frontiers in Neurorobotics ◽

10.3389/fnbot.2019.00047 ◽

2019 ◽

Vol 13 ◽

Cited By ~ 3

Author(s):

Zhihao Xu ◽

Xuefeng Zhou ◽

Shuai Li

Keyword(s):

Neural Networks ◽

Obstacle Avoidance ◽

Recurrent Neural Networks ◽

Redundant Manipulators ◽

Avoidance Control

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Decentralized control of collaborative redundant manipulators with partial command coverage via locally connected recurrent neural networks

Neural Computing and Applications ◽

10.1007/s00521-012-1030-2 ◽

2012 ◽

Vol 23 (3-4) ◽

pp. 1051-1060 ◽

Cited By ~ 48

Author(s):

Shuai Li ◽

Hongzhu Cui ◽

Yangming Li ◽

Bo Liu ◽

Yuesheng Lou

Keyword(s):

Neural Networks ◽

Decentralized Control ◽

Recurrent Neural Networks ◽

Redundant Manipulators

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Obstacle Avoidance Behaviors for Mobile Robots Using Genetic Algorithms and Recurrent Neural Networks

IFAC Proceedings Volumes ◽

10.3182/20130911-3-br-3021.00100 ◽

2013 ◽

Vol 46 (24) ◽

pp. 141-146 ◽

Cited By ~ 4

Author(s):

Jesus Savage ◽

S. Muñoz ◽

Mauricio Matamoros ◽

Roman Osorio

Keyword(s):

Neural Networks ◽

Genetic Algorithms ◽

Mobile Robots ◽

Obstacle Avoidance ◽

Recurrent Neural Networks ◽

Avoidance Behaviors

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Decentralized kinematic control of a class of collaborative redundant manipulators via recurrent neural networks

Neurocomputing ◽

10.1016/j.neucom.2012.01.034 ◽

2012 ◽

Vol 91 ◽

pp. 1-10 ◽

Cited By ~ 96

Author(s):

Shuai Li ◽

Sanfeng Chen ◽

Bo Liu ◽

Yangming Li ◽

Yongsheng Liang

Keyword(s):

Neural Networks ◽

Recurrent Neural Networks ◽

Redundant Manipulators ◽

Kinematic Control

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Terminal Recurrent Neural Networks for Time-Varying Reciprocal Solving With Application to Trajectory Planning of Redundant Manipulators

IEEE Transactions on Systems Man and Cybernetics Systems ◽

10.1109/tsmc.2020.2998485 ◽

2020 ◽

pp. 1-13

Author(s):

Ying Kong ◽

Yunliang Jiang ◽

Xiaoyun Xia

Keyword(s):

Neural Networks ◽

Trajectory Planning ◽

Recurrent Neural Networks ◽

Redundant Manipulators ◽

Time Varying

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RECURRENT NEURAL NETWORKS FOR REAL-TIME COMPUTATION OF INVERSE KINEMATICS OF REDUNDANT MANIPULATORS

Advances in Fuzzy Systems — Applications and Theory - Machine Intelligence: Quo Vadis? ◽

10.1142/9789812562531_0020 ◽

2004 ◽

pp. 299-319 ◽

Cited By ~ 14

Author(s):

JUN WANG ◽

YUNONG ZHANG

Keyword(s):

Neural Networks ◽

Real Time ◽

Recurrent Neural Networks ◽

Inverse Kinematics ◽

Redundant Manipulators

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Obstacle avoidance of redundant manipulators using neural networks based reinforcement learning

Robotics and Computer-Integrated Manufacturing ◽

10.1016/j.rcim.2011.07.004 ◽

2011 ◽

Cited By ~ 12

Author(s):

Mihai Duguleana ◽

Florin Grigore Barbuceanu ◽

Ahmed Teirelbar ◽

Gheorghe Mogan

Keyword(s):

Neural Networks ◽

Reinforcement Learning ◽

Obstacle Avoidance ◽

Redundant Manipulators

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Navigation and obstacle avoidance in an unstructured environment Videogame through recurrent neural networks continuous time (CTRNN)

2012 7th Colombian Computing Congress (CCC) ◽

10.1109/colombiancc.2012.6398004 ◽

2012 ◽

Cited By ~ 1

Author(s):

S. M. Ruiz ◽

L. F. Castillo ◽

Manuel Glez Bedia ◽

Gustavo A. Isaza

Keyword(s):

Neural Networks ◽

Obstacle Avoidance ◽

Recurrent Neural Networks ◽

Continuous Time ◽

Unstructured Environment

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Inverse Kinematics of Redundant Manipulators Formulated as Quadratic Programming Optimization Problem Solved Using Recurrent Neural Networks: A Review

Robotica ◽

10.1017/s0263574719001590 ◽

2019 ◽

Vol 38 (8) ◽

pp. 1495-1512

Author(s):

Ahmed A. Hassan ◽

Mohamed El-Habrouk ◽

Samir Deghedie

Keyword(s):

Neural Networks ◽

Quadratic Programming ◽

Recurrent Neural Networks ◽

Inverse Kinematics ◽

Optimization Problem ◽

Problem Formulation ◽

Joint Space ◽

Problem Solution ◽

Redundant Manipulators ◽

Joint Angles

SUMMARYThe Inverse Kinematics (IK) problem of manipulators can be divided into two distinct steps: (1) Problem formulation, where the problem is developed into a form which can then be solved using various methods. (2) Problem solution, where the IK problem is actually solved by producing the values of different joint space variables (joint angles, joint velocities or joint accelerations). The main focus of this paper is concentrated on the discussion of the IK problem of redundant manipulators, formulated as a quadratic programming optimization problem solved by different kinds of recurrent neural networks.

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