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Main Authors: Yao, Kanzhong, Marjanovic, Ognjen, Watson, Simon
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2403.10759
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author Yao, Kanzhong
Marjanovic, Ognjen
Watson, Simon
author_facet Yao, Kanzhong
Marjanovic, Ognjen
Watson, Simon
contents Navigation in cluttered underwater environments is challenging, especially when there are constraints on communication and self-localisation. Part of the fully distributed underwater navigation problem has been resolved by introducing multi-agent robot teams [1], however when the environment becomes cluttered, the problem remains unresolved. In this paper, we first studied the connection between everyday activity of dog walking and the cooperative underwater obstacle avoidance problem. Inspired by this analogy, we propose a novel dog walking paradigm and implement it in a multi-agent underwater system. Simulations were conducted across various scenarios, with performance benchmarked against traditional methods utilising Image-Based Visual Servoing in a multi-agent setup. Results indicate that our dog walking-inspired paradigm significantly enhances cooperative behavior among agents and outperforms the existing approach in navigating through obstacles.
format Preprint
id arxiv_https___arxiv_org_abs_2403_10759
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Fully Distributed Cooperative Multi-agent Underwater Obstacle Avoidance
Yao, Kanzhong
Marjanovic, Ognjen
Watson, Simon
Robotics
Navigation in cluttered underwater environments is challenging, especially when there are constraints on communication and self-localisation. Part of the fully distributed underwater navigation problem has been resolved by introducing multi-agent robot teams [1], however when the environment becomes cluttered, the problem remains unresolved. In this paper, we first studied the connection between everyday activity of dog walking and the cooperative underwater obstacle avoidance problem. Inspired by this analogy, we propose a novel dog walking paradigm and implement it in a multi-agent underwater system. Simulations were conducted across various scenarios, with performance benchmarked against traditional methods utilising Image-Based Visual Servoing in a multi-agent setup. Results indicate that our dog walking-inspired paradigm significantly enhances cooperative behavior among agents and outperforms the existing approach in navigating through obstacles.
title Fully Distributed Cooperative Multi-agent Underwater Obstacle Avoidance
topic Robotics
url https://arxiv.org/abs/2403.10759