Automated Design of Manipulators for In-Hand Tasks

Abstract

Grasp planning and motion synthesis for dexterous manipulation tasks are traditionally done given a preexisting kinematic model for the robotic hand. In this paper, we introduce a framework for automatically designing hand topologies best suited for manipulation tasks given high level objectives as input. Our goal is to create a pipeline that automatically generates custom hands designed for specific manipulation tasks based on high level user input. Our framework comprises of a sequence of trajectory optimizations chained together to translate a sequence of objective poses into an optimized hand mechanism along with a physically feasible motion plan involving both the constructed hand and the object. We demonstrate the feasibility of this approach by synthesizing a series of hand designs optimized to perform specified in-hand manipulation tasks of varying difficulty.