Multi-Sensor Fusion and Multi-Agent Control for Autonomous Environmental Exploration With Rat Robots
Haobo Xie, Haoze Xu, Kedi Xu, Wei Yang, Zesheng Yao, Canjun Yang
Abstract
This letter presents a bio-robotic multi-agent framework that integrates multi-sensor fusion with multi-agent control strategies for rat robots. The sensors equipped with rat robots, including laser-ranging sensor, camera and infrared sensor. We develop two multi-agent control strategies: a leader-follower strategy, in which one rat robot is designated as leader and utilizes lateral laser ranging sensor to navigate along boundaries, while others follow in formation; and a distributed strategy that enables all rat robots to perform decentralized decision-making exploration. The experimental platform consists of four rat robots operating in a confined indoor environment. Results demonstrate that multi-modal sensing significantly enhances environmental perception, particularly in confined and complex conditions; and both strategies provide stable and predictable cooperative motions and improves the efficiency and robustness of rat robot exploration. This work contributes an integrated bio-robotic multi-agent architecture that leverages multi-sensor perception and multi-agent control, offering a foundation for future applications in biological intelligence research, micro-scale environmental exploration and autonomous animal-machine systems.
BibTeX
@inproceedings{ral2026_multisensorfusio,
title = {Multi-Sensor Fusion and Multi-Agent Control for Autonomous Environmental Exploration With Rat Robots},
author = {Haobo Xie and Haoze Xu and Kedi Xu and Wei Yang and Zesheng Yao and Canjun Yang},
booktitle = {RA-L 2026},
year = {2026}
}