DocumentCode :
2144626
Title :
An improved Tangent Bug method integrated with artificial potential field for multi-robot path planning
Author :
Mohamed, Emam Fathy ; El-Metwally, Khaled ; Hanafy, A.R.
Author_Institution :
Arab Acad. for Sci. & Technol., Cairo, Egypt
fYear :
2011
fDate :
15-18 June 2011
Firstpage :
555
Lastpage :
559
Abstract :
This paper introduces the utilization of the wall following concept for path planning of multi-robots and proposes an improved Tangent Bug method to avoid falling in local minima encountered by the artificial potential field (APF) method used in real-time path planning. In the new algorithm, more reliable switching and merging conditions are designed to guarantee the success of escape. This method controls a team of robots with a deformable geometry, compliant with nearby static or dynamic obstacles including those represented by each robot team-mates. The robots are virtually linked to each other by the influence of artificial potentials that asymptotically stabilize the formation and keep all the robots separated by specified distances. Simulation studies have been carried out to verify the validity of the proposed method.
Keywords :
asymptotic stability; collision avoidance; mobile robots; multi-robot systems; APF method; artificial potential field; asymptotic stability; deformable geometry; dynamic obstacle; merging condition; multirobot path planning; real-time path planning; reliable switching condition; robot teammate; static obstacle; tangent bug method; wall following concept; Algorithm design and analysis; Heuristic algorithms; Path planning; Robot kinematics; Robot sensing systems; Switches; local minima; multi-robot systems; obstacle avoidance; potential field; tangent bug;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Innovations in Intelligent Systems and Applications (INISTA), 2011 International Symposium on
Conference_Location :
Istanbul
Print_ISBN :
978-1-61284-919-5
Type :
conf
DOI :
10.1109/INISTA.2011.5946136
Filename :
5946136
Link To Document :
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