Modified bug-1 algorithm based strategy for obstacle avoidance in multi robot system

Author:

Kandathil Jom J.,Mathew Robins,Hiremath Somashekhar S.

Abstract

One of the primary ability of an intelligent mobile robot system is obstacle avoidance. BUG algorithms are classic examples of the algorithms used for achieving obstacle avoidance. Unlike many other planning algorithms based on global knowledge, BUG algorithms assume only local knowledge of the environment and a global goal. Among the variations of the BUG algorithms that prevail, BUG-0, BUG-1 and BUG-2 are the more prominent versions. The exhaustive search algorithm present in BUG-1 makes it more reliable and safer for practical applications. Overall, this provides a more predictable and dependable performance. Hence, the essential focus in this paper is on implementing the BUG-1 algorithm across a group of robots to move them from a start location to a target location. The results are compared with the results from BUG-1 algorithm implemented on a single robot. The strategy developed in this work reduces the time involved in moving the robots from starting location to the target location. Further, the paper shows that the total distance covered by each robot in a multi robot-system is always lesser than or equal to that travelled by a single robot executing the same problem.

Publisher

EDP Sciences

Subject

General Medicine

Reference9 articles.

1. Dynamic path planning for a mobile automaton with limited information on the environment

2. Zohaib M., Pasha S.M, Javaid N., Iqbal J., International multi topic conference, 291-299 (2013)

3. Langer R. A., Coelho L. S., Oliveira G.H, IEEE Inernational. Conference on control application, 403-408 (2007)

4. Ng J., Braunl T., J. of Intelligent and Robotic Systems, 50,1(2007)

5. T. Facchinetti, t-bots: a coordinated team of mobile units for searching and occupying a target area at unknown location

Cited by 1 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

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