Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/145712
Title: A discrete event formulation for multi-robot collision avoidance on pre-planned trajectories
Authors: Deplano, Diego
Franceschelli, Mauro
Ware, Simon
Rong, Su
Giua, Alessandro
Keywords: Engineering::Electrical and electronic engineering
Issue Date: 2020
Source: Deplano, D., Franceschelli, M., Ware, S., Rong, S., & Giua, A. (2020). A discrete event formulation for multi-robot collision avoidance on pre-planned trajectories. IEEE Access, 8, 92637-92646. doi:10.1109/access.2020.2994472
Journal: IEEE Access
Abstract: In this paper we consider the problem of collision avoidance among robots that follow pre-planned trajectories in a structured environment while minimizing the maximum traveling time among them. More precisely, we consider a discrete event formulation of this problem. Robots are modeled by automata, the environment is partitioned into a square grid where cells represent free space, obstacles and walls, which are modeled as shared resources among robots. The main contribution of this paper is twofold. First, we propose a problem formulation based on mixed integer linear programming to compute an optimal schedule for the pre-planned trajectories. Second, we propose a heuristic method to compute a sub-optimal schedule: the computational complexity of this approach is shown to be polynomial with the number of robots and the dimension of the environment. Finally, simulations are provided to validate performance and scalability of the proposed approach.
URI: https://hdl.handle.net/10356/145712
ISSN: 2169-3536
DOI: 10.1109/ACCESS.2020.2994472
Rights: © 2020 IEEE. This journal is 100% open access, which means that all content is freely available without charge to users or their institutions. All articles accepted after 12 June 2019 are published under a CC BY 4.0 license, and the author retains copyright. Users are allowed to read, download, copy, distribute, print, search, or link to the full texts of the articles, or use them for any other lawful purpose, as long as proper attribution is given.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Journal Articles

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