Finding shorter paths for robot arms using their redundancy

TL;DR

This paper introduces a method that leverages the redundancy in robot arm configurations to find shorter, faster paths, significantly improving execution times in practical tasks like grape vine pruning.

Contribution

It presents a novel approach to utilize multiple goal configurations for robot arms, resulting in shorter, more efficient paths compared to traditional single-goal planning.

Findings

Reduced execution times by 58% in grape vine pruning robot experiment

Achieved significantly shorter paths using multiple goal configurations

Demonstrated practical benefits in real-world robotic tasks

Abstract

Many robot arms can accomplish one task using many different joint configurations. Often only one of these configurations is used as a goal by the path planner. Ideally the robot's path planner would be able to use the extra configurations to find higher quality paths. In this paper we use the extra goal configurations to find significantly shorter paths that are faster to execute compared to a planner that chooses one goal configuration arbitrarily. In a grape vine pruning robot arm experiment our proposed approach reduced execution times by 58%.