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Recent research in cooperative path planning algorithms for multi-agent using mixed-integer linear programming

Che Ku Melor, C. K. N. A. H. and Omar, R. and Sabudin, E. N. (2016) Recent research in cooperative path planning algorithms for multi-agent using mixed-integer linear programming. ARPN Journal of Engineering and Applied Sciences, 11 (14). pp. 8921-8926. ISSN 18196608

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Abstract

Path planning is one of the issues to be handled in the development of autonomous systems. For a group of agents, cooperative path planning is crucial to ensure that a given mission is accomplished in the shortest time possible with optimal solution. Optimal means that the resulting path has minimal length hence thetotal consumed energy by the agents is the least. Cooperative path planning fuses information from all agents to plan an optimal path. There are a number of cooperative path planning methods available in the literature for multi-agent including Cell Decomposition, Roadmap and Potential Field to name but three. This paper will review and compare the performances of those existing methods that can find solution without graph search algorithm such as Mixed-Integer Linear Programming (MILP) techniques which exactly solves the problem and then propose four alternative MILP formulations which are computationally less intensive and suited for real-time purposes, but yield a theoretically guaranteed suboptimal solution.

Item Type: Article
Uncontrolled Keywords: Path planning; mixed-integer linear programming
Subjects: Q Science > QA Mathematics > QA76 Computer software
Divisions: Faculty of Electrical and Electronic Engineering > Department of Robotic and Mechatronic Engineering
Depositing User: Mr. Mohammad Shaifulrip Ithnin
Date Deposited: 13 Aug 2018 03:27
Last Modified: 13 Aug 2018 03:27
URI: http://eprints.uthm.edu.my/id/eprint/9973
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