Efficient prioritized inverse kinematic solutions for redundant manipulators

Abstract

In this paper, we explore preprocessing techniques aimed at efficiently mapping the workspace to the configuration space for redundant manipulators. Exploiting the increasing availability of memory we precompute a database for online use that allows fast querying of joint configurations with high manipulability. Such a system is useful for performing reaching and manipulation tasks, online force control, and quickly computing goal configurations for path planning algorithms. We have implemented a prototype system on the digital human version humanoid robot platform 2 (DH-HRP2) which we use to efficiently compute arm inverse kinematic solutions. We demonstrate the benefits of such a system applied to converting workspace trajectories to configuration space trajectories. Although we have applied the technique to finding joint configurations with high manipulability, our approach can be generalized to a variety of different priority measures that may be used for evaluating inverse kinematic solutions for redundant manipulators.