2024/11/01 by Muhammad Fadhil Ginting, Kyohei Otsu, Ginting, Muhammad Fadhil +5 · 1 citation
Business, Management and Accounting · Decision Sciences · Psychology · #Big Data and Business Intelligence #FOS: Computer and information sciences #Robotics (cs.RO) #Scientific Computing and Data Management #Team Dynamics and Performance
paper · pdf · doi:10.48550/arxiv.2411.00400
openalex publication_date 2024/11/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
To achieve autonomy in complex real-world exploration missions, we consider deployment strategies for a team of robots with heterogeneous autonomy capabilities. In this work, we formulate a multi-robot exploration mission and compute an operation policy to maintain robot team productivity and maximize mission rewards. The environment description, robot capability, and mission outcome are modeled as a Markov decision process (MDP). We also include constraints in real-world operation, such as sensor failures, limited communication coverage, and mobility-stressing elements. Then, we study the proposed operation model on a real-world scenario in the context of the DARPA Subterranean (SubT) Challenge. The computed deployment policy is also compared against the human-based operation strategy in the final competition of the SubT Challenge. Finally, using the proposed model, we discuss the design trade-off on building a multi-robot team with heterogeneous capabilities.