TY - GEN
T1 - Research on singular robustness algorithm of robot inverse kinematics based on dynamic damping coefficient
AU - Liu, Peng
AU - Yu, Dianyong
AU - Li, Ruifeng
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/11/27
Y1 - 2017/11/27
N2 - In order to solve the singularity problem of the Jacobian matrix in the robotic inverse kinematics method, a new singular processing algorithm is proposed. Based on the damped least-square (DLS) method, the damping coefficients, by using the singular value decomposition (SVD) of the Jacobian matrix, are optimized from the fixed value of the traditional algorithm to the dynamic value adjusted with the Jacobian matrix. It is ensured that the angular velocity curve of each joint is continuous and smooth when the robot passes through the singularity, and the robustness of the inverse solution algorithm is enhanced. The algorithm is simulated on the Kawasaki BA006N robot, results show that the robot does not introduce the tracking error at the non-singular position. At the singular position, the joint motion of the robot is smooth and the singular robustness is better than that of the existing algorithm.
AB - In order to solve the singularity problem of the Jacobian matrix in the robotic inverse kinematics method, a new singular processing algorithm is proposed. Based on the damped least-square (DLS) method, the damping coefficients, by using the singular value decomposition (SVD) of the Jacobian matrix, are optimized from the fixed value of the traditional algorithm to the dynamic value adjusted with the Jacobian matrix. It is ensured that the angular velocity curve of each joint is continuous and smooth when the robot passes through the singularity, and the robustness of the inverse solution algorithm is enhanced. The algorithm is simulated on the Kawasaki BA006N robot, results show that the robot does not introduce the tracking error at the non-singular position. At the singular position, the joint motion of the robot is smooth and the singular robustness is better than that of the existing algorithm.
KW - Damped leastsquare( DLS)
KW - Inverse kinematics
KW - Jacobian matrix
KW - Singular robustness
KW - Singular value decomposition(SVD)
UR - https://www.scopus.com/pages/publications/85043303018
U2 - 10.1109/ITOEC.2017.8122412
DO - 10.1109/ITOEC.2017.8122412
M3 - 会议稿件
AN - SCOPUS:85043303018
T3 - Proceedings of 2017 IEEE 3rd Information Technology and Mechatronics Engineering Conference, ITOEC 2017
SP - 204
EP - 209
BT - Proceedings of 2017 IEEE 3rd Information Technology and Mechatronics Engineering Conference, ITOEC 2017
A2 - Xu, Bing
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 3rd IEEE Information Technology and Mechatronics Engineering Conference, ITOEC 2017
Y2 - 3 October 2017 through 5 October 2017
ER -