This paper introduces a novel method for the coordinated control of heterogeneous multi-robot systems composed of a UGV and a UAV and focuses on cooperative exploration in unknown environments. The proposed approach utilizes a numerical optimization solver to manage the non-linear dynamics and constraints of both agents. We introduce a weighting parameter to adapt the team behavior either prioritizing proximity between the agents or independently pursuing the exploration. The proposed solution has been extensively tested in a simulation environment and the experimental results demonstrate the method’s computational efficiency, adaptability, and suitability for real-time deployment in autonomous exploration missions. This approach advances multi-robot coordination by providing a flexible and robust framework for heterogeneous agent collaboration in complex, unstructured environments.

Heterogeneous Multi-robot Systems Cooperative Exploration of Unknown Environment

Mugnai M.;Satler M.
Co-primo
;
Avizzano C. A.
2025-01-01

Abstract

This paper introduces a novel method for the coordinated control of heterogeneous multi-robot systems composed of a UGV and a UAV and focuses on cooperative exploration in unknown environments. The proposed approach utilizes a numerical optimization solver to manage the non-linear dynamics and constraints of both agents. We introduce a weighting parameter to adapt the team behavior either prioritizing proximity between the agents or independently pursuing the exploration. The proposed solution has been extensively tested in a simulation environment and the experimental results demonstrate the method’s computational efficiency, adaptability, and suitability for real-time deployment in autonomous exploration missions. This approach advances multi-robot coordination by providing a flexible and robust framework for heterogeneous agent collaboration in complex, unstructured environments.
2025
9783031894701
9783031894718
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11382/584540
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