A Redundancy Resolution Method for Robot with Multi-Constraints Based on the Varied Weighted Least-Norm Principle

Abstract

In order to compute the redundancy-resolution for robots with multi-constraints, an approximate method based on weighted least-norm principle is presented. With this method, different constraints is assigned with corresponding coefficients, and the cost function is given out and optimized for the best between the accuracy and the fulfillment of the constraint, which is based on the weighted least-norm of each constraints and the main task. Firstly, the state of the art of redundant resolution is introduced in brief and the drawback with the application to the resolution with multi-constraints is pointed out. Then the redundancy resolution at velocity level and position level, and the modeling of the constraints are proposed. In view of this, the weighted least-norm method is presented. Finally, the effectiveness of the proposed method is demonstrated by simulations of a six-DoFs biped walking robot Bibot-U6 with the stability constraint and joint limits constraints. The result shows that the method has an excellent robustness for the under-determined system and over-determined system, meanwhile has a good accuracy.