TY - GEN
T1 - A novel recurrent neural network for improving redundant manipulator motion planning completeness
AU - Li, Yangming
AU - Li, Shuai
AU - Hannaford, Blake
PY - 2018/9/10
Y1 - 2018/9/10
N2 - Recurrent Neural Networks (RNNs) demonstrated advantages on control precision, system robustness and computational efficiency, and have been widely applied to redundant manipulator control optimization. Existing RNN control schemes locally optimize trajectories and are efficient and reliable on obstacle avoidance. However, for motion planning, they suffer from local minimum and do not have planning completeness. This work explained the cause of the planning incompleteness and addressed the problem with a novel RNN control scheme. The paper presented the proposed method in detail and analyzed the global stability and the planning completeness in theory. The proposed method was compared with other three control schemes on the precision, the robustness and the planning completeness in software simulation and the results shows the proposed method has improved precision and robustness, and planning completeness.
AB - Recurrent Neural Networks (RNNs) demonstrated advantages on control precision, system robustness and computational efficiency, and have been widely applied to redundant manipulator control optimization. Existing RNN control schemes locally optimize trajectories and are efficient and reliable on obstacle avoidance. However, for motion planning, they suffer from local minimum and do not have planning completeness. This work explained the cause of the planning incompleteness and addressed the problem with a novel RNN control scheme. The paper presented the proposed method in detail and analyzed the global stability and the planning completeness in theory. The proposed method was compared with other three control schemes on the precision, the robustness and the planning completeness in software simulation and the results shows the proposed method has improved precision and robustness, and planning completeness.
KW - Kinematic Control
KW - Motion Planning
KW - Recurrent Neural Networks
KW - Redundant Manipulator
KW - Robot
UR - http://www.scopus.com/inward/record.url?scp=85062976764&partnerID=8YFLogxK
U2 - 10.1109/ICRA.2018.8461204
DO - 10.1109/ICRA.2018.8461204
M3 - Conference article published in proceeding or book
AN - SCOPUS:85062976764
T3 - Proceedings - IEEE International Conference on Robotics and Automation
SP - 2956
EP - 2961
BT - 2018 IEEE International Conference on Robotics and Automation, ICRA 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2018 IEEE International Conference on Robotics and Automation, ICRA 2018
Y2 - 21 May 2018 through 25 May 2018
ER -