Task-Based Design of Ad-hoc Modular Manipulators.

Thais Campos, Jeevana Priya Inala, Armando Solar-Lezama, Hadas Kress-Gazit

Abstract: The great promise of modular robots is the ability to create on demand robots; however, choosing the “right” design based on a task is still a challenging problem. In this paper, we present an approach to automatically synthesize both the design and control for modular robots from a task description. In particular, we focus on manipulators composed of one degree-of-freedom (DoF) modules. Our approach is able to handle partially infeasible tasks by either identifying the infeasible part and finding a design that satisfies the feasible part or searching for multiple designs that together satisfy the entire task. We compare our approach to a baseline genetic algorithm in a series of increasingly complex environments.