A new neural network learning of inverse kinematics of robot manipulator
Yasuaki Kuroe, Yuki Nakai, Taketoshi Mori
- 发表年份
- 2002
- 引用次数
- 23
摘要
In this paper we present a new method of solving the inverse kinematics of robot manipulators. We propose a learning method of a neural network such that the network represents the relations of both the positions and velocities from the task space coordinate to the joint space coordinate simultaneously. The adjoint neural networks for the original neural networks are introduced in order to derive the efficient learning algorithm. It is shown that the proposed method makes it possible to solve the inverse kinematics problem of robot manipulators more accurately.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
关键词
相关论文
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
A new optimizer using particle swarm theory
R.C. Eberhart, James Kennedy
2002