2023/06/07 by Vu Phi Tran, Asanka G. Perera, Tran, Vu Phi +7
Agricultural and Biological Sciences · Computer Science · Engineering · #FOS: Computer and information sciences #Insect Pheromone Research and Control #Modular Robots and Swarm Intelligence #Multiagent Systems (cs.MA) #Robotic Path Planning Algorithms #Robotics (cs.RO)
paper · pdf · doi:10.48550/arxiv.2306.04083
openalex publication_date 2023/06/07 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
This paper proposes a state-machine model for a multi-modal, multi-robot environmental sensing algorithm. This multi-modal algorithm integrates two different exploration algorithms: (1) coverage path planning using variable formations and (2) collaborative active sensing using multi-robot swarms. The state machine provides the logic for when to switch between these different sensing algorithms. We evaluate the performance of the proposed approach on a gas source localisation and mapping task. We use hardware-in-the-loop experiments and real-time experiments with a radio source simulating a real gas field. We compare the proposed approach with a single-mode, state-of-the-art collaborative active sensing approach. Our results indicate that our multi-modal switching approach can converge more rapidly than single-mode active sensing.