TY - GEN
T1 - The Playback Trajectory Optimization Algorithm for Collaborative Robot
AU - Chen, Youdong
AU - Feng, Qiangguo
AU - Guo, Jiaxin
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/7/2
Y1 - 2018/7/2
N2 - Teaching is a basic function of many collaborative robots. The recorded trajectories with teaching may contain noises and jumps due to hand trembling and sensor errors. When the robot replays these trajectories, these noises and jumps may cause vibrations and shocks, even damage the body of the robot. An algorithm based on CHOMP (Covariant Hamiltonian Optimization for Motion Planning) algorithm is proposed to optimize the playback trajectories of collaborative robot. The algorithm is composed of two norms in the Hilbert space. One Euclidian norm is used for the evaluation of the replay of trajectories. The other norm that combines the first and second order derivatives of trajectories is used for the evaluation of trajectory dynamic characters. Experiments of UR3 robot in both obstacle-free and obstacle environments prove that the proposed algorithm can optimize the recorded trajectories of a collaborative robot as well as enabling the trajectory to maintain useful.
AB - Teaching is a basic function of many collaborative robots. The recorded trajectories with teaching may contain noises and jumps due to hand trembling and sensor errors. When the robot replays these trajectories, these noises and jumps may cause vibrations and shocks, even damage the body of the robot. An algorithm based on CHOMP (Covariant Hamiltonian Optimization for Motion Planning) algorithm is proposed to optimize the playback trajectories of collaborative robot. The algorithm is composed of two norms in the Hilbert space. One Euclidian norm is used for the evaluation of the replay of trajectories. The other norm that combines the first and second order derivatives of trajectories is used for the evaluation of trajectory dynamic characters. Experiments of UR3 robot in both obstacle-free and obstacle environments prove that the proposed algorithm can optimize the recorded trajectories of a collaborative robot as well as enabling the trajectory to maintain useful.
UR - https://www.scopus.com/pages/publications/85064126844
U2 - 10.1109/ROBIO.2018.8664765
DO - 10.1109/ROBIO.2018.8664765
M3 - 会议稿件
AN - SCOPUS:85064126844
T3 - 2018 IEEE International Conference on Robotics and Biomimetics, ROBIO 2018
SP - 1671
EP - 1676
BT - 2018 IEEE International Conference on Robotics and Biomimetics, ROBIO 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2018 IEEE International Conference on Robotics and Biomimetics, ROBIO 2018
Y2 - 12 December 2018 through 15 December 2018
ER -