Title :
Obstacle avoidance inverse kinematics solution of redundant manipulators by neural networks
Author :
Hsia, T.C. ; Mao, Ziqiang
Author_Institution :
Dept. of Electr. Eng. & Comput. Sci., California Univ., Davis, CA, USA
Abstract :
Summary form only given. A neural network scheme is proposed to solve the inverse kinematic problem for redundant robots in an environment with or without obstacles. The inverse kinematic solution of a four link planar robot is simulated using a multilayer feedforward network with hidden units having sigmoidal functions and output units having linear functions. The results show that the proposed scheme provides very satisfactory solutions
Keywords :
feedforward neural nets; inverse problems; kinematics; redundancy; robots; four link planar robot; linear functions; multilayer feedforward network; neural networks; obstacle avoidance inverse kinematics solution; redundant manipulators; sigmoidal functions; Delta modulation; Manipulators; Multi-layer neural network; Neural networks; Orbital robotics; Q measurement; Robot kinematics;
Conference_Titel :
Robotics and Automation, 1993. Proceedings., 1993 IEEE International Conference on
Conference_Location :
Atlanta, GA
Print_ISBN :
0-8186-3450-2
DOI :
10.1109/ROBOT.1993.291813
