Optimal Robot Path Planning In a Collaborative Human-Robot Team with Intermittent Human Availability

TL;DR

This paper introduces an optimal path planning method for robots operating in environments with intermittent human assistance, balancing speed and waiting constraints to improve efficiency in collaborative tasks.

Contribution

It presents a novel approach using budget and critical departure times to compute optimal paths, scalable to larger problems than previous methods.

Findings

Outperforms baseline algorithms in city road network scenarios

Effectively incorporates human availability constraints into planning

Provides scalable solutions for real-world robot-human collaboration

Abstract

This paper presents a solution for the problem of optimal planning for a robot in a collaborative human-robot team, where the human supervisor is intermittently available to assist the robot in completing tasks more quickly. Specifically, we address the challenge of computing the fastest path between two configurations in an environment with time constraints on how long the robot can wait for assistance. To solve this problem, we propose a novel approach that utilizes the concepts of budget and critical departure times, which enables us to obtain optimal solutions while scaling to larger problem instances than existing methods. We demonstrate the effectiveness of our approach by comparing it with several baseline algorithms on a city road network and analyzing the quality of the solutions obtained. Our work contributes to the field of robot planning by addressing the critical issue of incorporating human assistance and environmental restrictions, which has significant implications for real-world applications.