Minimum-Effort Task-based Design Optimization of Modular Reconfigurable Robots

Abstract

The flexibility and adaptability of modular and re-configurable robots opens up new opportunities for on-demand robot morphology optimization for varying tasks. In particular, multi-arm robotic systems can expand the solution space for any given task. In this paper, we present a novel approach to exploit this feature for generating optimal fit-to-task robot structures with respect to a minimum-effort objective. By describing the task in terms of relative poses between the end-effector and the constraint frame, and making use of the relative Jacobian, the minimum effort optimization problem can be equally expressed for single-arm or multi-arm robots. We test our approach for a peg-in-hole and a contour-following task and compare the performance of the optimal solution obtained with that of a standard manipulator configuration.