首页 /研究 /Robot trajectory control using neural networks-theory and PUMA simulations
MANIPULATION

Robot trajectory control using neural networks-theory and PUMA simulations

Y. Jin, Tony Pipe, Alan Winfield

发表年份
2002
引用次数
9

摘要

In this paper we investigate neural network applications in trajectory control of robotic manipulators. Most research in the field remains at an empirical level. Although other authors have claimed very good simulation or even experiment results, lack of theoretical guarantee prevents application of the results in industry. In contrast, this paper presents a neural control method which has a strict theoretical basis. The whole system (manipulator and neural network) stability is guaranteed. Simulations in PUMA robot applications are also presented.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

关键词

TrajectoryArtificial neural networkRobotComputer scienceStability (learning theory)Control (management)Field (mathematics)Control engineeringArtificial intelligenceRobot control

相关论文

查看 MANIPULATION 分类全部论文