Multi-robot patrol

Author:

Yan Chuanbo1,Zhang Tao1

Affiliation:

1. Department of Automation, Tsinghua University, Beijing, China

Abstract

Multi-robot with advantages of spatial distribution and fault tolerance is competent for patrol missions and has the potential to be used in security and surveillance applications. This article focuses on the frequency-based patrol designed to guarantee the frequent access to key positions in the environment. A distributed algorithm based on expected idleness is proposed, aiming to promote the efficiency of cooperation, which remains to be fault tolerant and scalable. The expected idleness is estimated with information shared between robots and utilized to avoid conflicts in the decision process. Comparisons with state-of-the-art algorithms have been conducted in a realistic simulator, Stage; moreover, the fault tolerance and scalability have also been tested. Experiments on real robots have further verified the applicability of the proposed algorithm.

Publisher

SAGE Publications

Subject

Artificial Intelligence,Computer Science Applications,Software

Cited by 20 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Efficient Communication for Pursuit-Evasion Games with Asymmetric Information;2023 62nd IEEE Conference on Decision and Control (CDC);2023-12-13

2. Enchères pour le Maintien des Communications lors de l’Allocation de Tâches pour des Missions Multi-robots;Revue Ouverte d'Intelligence Artificielle;2023-07-04

3. Adaptive Expected Reactive algorithm for Heterogeneous Patrolling Systems based on Target Uncertainty;2023 IEEE 47th Annual Computers, Software, and Applications Conference (COMPSAC);2023-06

4. Path planning and search effectiveness of USV based on underwater target scattering model;Journal of Physics: Conference Series;2023-06-01

5. Target Defense against Periodically Arriving Intruders;2023 American Control Conference (ACC);2023-05-31

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3