Trajectory Planning of a Manipulator in Joint Space Based on RBF Neural Network
In this paper,a new methodology for optimal trajectory planning of robotic manipulator in the joint space has been described,The RBF neuraI network is used for general approaching problem of nonlinear mapping in the joint space.A single.input and six-output RBF neural network model is built and trained.The data got from the jnverse kinematics equation are used as training samples and the interpolating calculation was completed in 6-dimension ioint space.With characters of rapid convergence and weil approximation,this new algorithm is faiult tolerant and irrelative with order of inputs,which can ensure the result trajectory is smooth enough.The algorithm has been tested in simulation in the software ADAMS,yielding good results by studying the kinematics and the dynamics perfcIrmance of the robot.
joint space RBF neural network trajectory planning
Qingwen Qu Jixiang Wan
国际会议
The International Conference Information Computing and Automation(2007国际信息计算与自动化会议)
成都
英文
460-463
2007-12-19（万方平台首次上网日期，不代表论文的发表时间）