A Hybrid Evolutionary Approach for Multi Robot Coordinated Planning at Intersections

Fuente: arXiv
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Autore principale: Parque, Victor
Natura: Preprint
Pubblicazione: 2024
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author Parque, Victor
author_facet Parque, Victor
contents Coordinated multi-robot motion planning at intersections is key for safe mobility in roads, factories and warehouses. The rapidly exploring random tree (RRT) algorithms are popular in multi-robot motion planning. However, generating the graph configuration space and searching in the composite tensor configuration space is computationally expensive for large number of sample points. In this paper, we propose a new evolutionary-based algorithm using a parametric lattice-based configuration and the discrete-based RRT for collision-free multi-robot planning at intersections. Our computational experiments using complex planning intersection scenarios have shown the feasibility and the superiority of the proposed algorithm compared to seven other related approaches. Our results offer new sampling and representation mechanisms to render optimization-based approaches for multi-robot navigation.
format Preprint
id arxiv_https___arxiv_org_abs_2412_01082
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle A Hybrid Evolutionary Approach for Multi Robot Coordinated Planning at Intersections
Parque, Victor
Robotics
Artificial Intelligence
Neural and Evolutionary Computing
Optimization and Control
Computation
Coordinated multi-robot motion planning at intersections is key for safe mobility in roads, factories and warehouses. The rapidly exploring random tree (RRT) algorithms are popular in multi-robot motion planning. However, generating the graph configuration space and searching in the composite tensor configuration space is computationally expensive for large number of sample points. In this paper, we propose a new evolutionary-based algorithm using a parametric lattice-based configuration and the discrete-based RRT for collision-free multi-robot planning at intersections. Our computational experiments using complex planning intersection scenarios have shown the feasibility and the superiority of the proposed algorithm compared to seven other related approaches. Our results offer new sampling and representation mechanisms to render optimization-based approaches for multi-robot navigation.
title A Hybrid Evolutionary Approach for Multi Robot Coordinated Planning at Intersections
topic Robotics
Artificial Intelligence
Neural and Evolutionary Computing
Optimization and Control
Computation
url https://arxiv.org/abs/2412.01082