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Autori principali: Ibrahimov, Roman, Heinen, Jannik Matthias
Natura: Preprint
Pubblicazione: 2025
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Accesso online:https://arxiv.org/abs/2510.06085
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author Ibrahimov, Roman
Heinen, Jannik Matthias
author_facet Ibrahimov, Roman
Heinen, Jannik Matthias
contents This project proposes a bioinspired multi-robot system using Distributed Optimization for efficient exploration and mapping of unknown environments. Each robot explores its environment and creates a map, which is afterwards put together to form a global 2D map of the environment. Inspired by wall-following behaviors, each robot autonomously explores its neighborhood based on a tactile sensor, similar to the antenna of a cockroach, mounted on the surface of the robot. Instead of avoiding obstacles, robots log collision points when they touch obstacles. This decentralized control strategy ensures effective task allocation and efficient exploration of unknown terrains, with applications in search and rescue, industrial inspection, and environmental monitoring. The approach was validated through experiments using e-puck robots in a simulated 1.5 x 1.5 m environment with three obstacles. The results demonstrated the system's effectiveness in achieving high coverage, minimizing collisions, and constructing accurate 2D maps.
format Preprint
id arxiv_https___arxiv_org_abs_2510_06085
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Multi-Robot Distributed Optimization for Exploration and Mapping of Unknown Environments using Bioinspired Tactile-Sensor
Ibrahimov, Roman
Heinen, Jannik Matthias
Robotics
This project proposes a bioinspired multi-robot system using Distributed Optimization for efficient exploration and mapping of unknown environments. Each robot explores its environment and creates a map, which is afterwards put together to form a global 2D map of the environment. Inspired by wall-following behaviors, each robot autonomously explores its neighborhood based on a tactile sensor, similar to the antenna of a cockroach, mounted on the surface of the robot. Instead of avoiding obstacles, robots log collision points when they touch obstacles. This decentralized control strategy ensures effective task allocation and efficient exploration of unknown terrains, with applications in search and rescue, industrial inspection, and environmental monitoring. The approach was validated through experiments using e-puck robots in a simulated 1.5 x 1.5 m environment with three obstacles. The results demonstrated the system's effectiveness in achieving high coverage, minimizing collisions, and constructing accurate 2D maps.
title Multi-Robot Distributed Optimization for Exploration and Mapping of Unknown Environments using Bioinspired Tactile-Sensor
topic Robotics
url https://arxiv.org/abs/2510.06085