Scheduling Operator Assistance for Shared Autonomy in Multi-Robot Teams

Conference paper (2022)

Authors

Yifan Cai University of Waterloo
Abhinav Dahiya University of Waterloo
N. Wilde Learning & Autonomous Control - Mechanical, Maritime and Materials Engineering
Stephen L. Smith University of Waterloo
Research Group
Learning & Autonomous Control (Mechanical, Maritime and Materials Engineering) (TU Delft)
Copyright: © 2022 Yifan Cai, Abhinav Dahiya, N. Wilde, Stephen L. Smith
DOI
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https://doi.org/10.1109/CDC51059.2022.9993014
Scheduling Numerical simulation Task analysis Autonomous robots Schedules
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Published Date

2022

Language

English

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Faculty

Mechanical, Maritime and Materials Engineering

Department

Cognitive Robotics

Research Group

Learning & Autonomous Control

Abstract

In this paper, we consider the problem of allocating human operator assistance in a system with multiple autonomous robots. Each robot is required to complete independent missions, each defined as a sequence of tasks. While executing a task, a robot can either operate autonomously or be teleoperated by the human operator to complete the task at a faster rate. We formulate our problem as a Mixed Integer Linear Program, which can be used to optimally solve small to moderate sized problem instances. We also develop an anytime algorithm that makes use of the problem structure to provide a fast and high-quality solution of the operator scheduling problem, even for larger problem instances. Our key insight is to identify blocking tasks in greedily-created schedules and iteratively remove those blocks to improve the quality of the solution. Through numerical simulations, we demonstrate the benefits of the proposed algorithm as an efficient and scalable approach that outperforms other greedy methods.