Obstacle avoidance of redundant manipulators using a dual neural network

Yunong Zhang, Jun Wang

Research output: Contribution to journalConference articlepeer-review

17 Citations (Scopus)

Abstract

One important issue in motion planning and kinematic control of redundant manipulators is the real-time obstacle avoidance. Following the previous researches [1]-[3], a new problem formulation has been proposed in the sense that the collision avoidance scheme is described by dynamically-updated inequality constraints, and that physical constraints such as joint limits are also incorporated in the formulation. For real-time computation, the dual neural network is applied for the online solution of obstacle-avoidance inverse-kinematic control problem, and then simulated based on the PA10 robot manipulator in the presence of obstacles.

Original languageEnglish
Pages (from-to)2747-2752
Number of pages6
JournalProceedings - IEEE International Conference on Robotics and Automation
Volume2
Publication statusPublished - 2003
Externally publishedYes
Event2003 IEEE International Conference on Robotics and Automation - Taipei, Taiwan, Province of China
Duration: 14 Sep 200319 Sep 2003

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