Preparatory Manipulation Planning using Automatically Determined Single and Dual Arms

TL;DR

This paper introduces an automated manipulation planning algorithm that determines optimal single or dual-arm sequences for reorienting objects, enhancing robotic task preparation in diverse scenarios.

Contribution

It presents a novel regrasp graph-based algorithm capable of automatically selecting single or dual-arm manipulation strategies for object reorientation tasks.

Findings

Successfully plans manipulation sequences for various robots.

Works in both simulation and real-world environments.

Automatically chooses between single and dual-arm approaches.

Abstract

This paper presents a manipulation planning algorithm for robots to reorient objects. It automatically finds a sequence of robot motion that manipulates and prepares an object for specific tasks. Examples of the preparatory manipulation planning problems include reorienting an electric drill to cut holes, reorienting workpieces for assembly, and reorienting cargo for packing, etc. The proposed algorithm could plan single and dual arm manipulation sequences to solve the problems. The mechanism under the planner is a regrasp graph which encodes grasp configurations and object poses. The algorithms search the graph to find a sequence of robot motion to reorient objects. The planner is able to plan both single and dual arm manipulation. It could also automatically determine whether to use a single arm, dual arms, or their combinations to finish given tasks. The planner is examined by various humanoid robots like Nextage, HRP2Kai, HRP5P, etc., using both simulation and real-world experiments.