Dynamic optimization of redundant manipulators in worst case using recurrent neural networks

The aim of this paper is to find a comprehensive dynamic performance index (CDPI) for evaluating dynamic merit, and to develop a procedure for the opt imization of dynamic performance for redundant manipulators in the worst ca se. CDPI stands for the maximum normalized joint driving torque and it can be minimized by linear programming. To obtain the minimum CDPI solution, a recurrent neural-network-based computational scheme is proposed for real ti me implementation. Robot configurations reached using the proposed planning algorithm can obtain the minimum joint driving torques. Numerical simulati ons have been carried out which illustrate good performance capability from the viewpoint of torque optimization. (C) 1999 Elsevier Science Ltd. Al ri ghts reserved.