Asymmetric Scout-Worker Reconnaissance for Route Validation in Unknown Environments

Abstract:This paper studies asymmetric scout-worker reconnaissance in unknown environments, where a small, agile autonomous scout explores routes for a larger worker robot that must visit an ordered sequence of goal locations. Because the scout has a smaller footprint and greater mobility, a scout-traversable route may be infeasible for the worker; worker feasibility must therefore be inferred from scout observations. This setting is not explicitly addressed by existing exploration and replanning methods, which typically assume a single traversability model and seek optimal paths for the same robot performing the exploration. We introduce a symbiotic scout-based framework that exploits the scout's superior mobility to explore only the portions of the unknown environment needed to identify worker-feasible path segments connecting the ordered goals. Evaluations in simulated and real-world settings demonstrate that the proposed approach validates feasible routes, repairs blocked segments with validated worker-feasible detours, and substantially reduces scout travel compared to baseline exploration and planning methods. A real-world indoor deployment further demonstrates the scout navigating narrow corridors to identify a worker-feasible route.

Robotics (cs.RO)

arXiv:2609.36537 [cs.RO]

(or arXiv:2609.36537v1 [cs.RO] for this version)

https://doi.org/10.48550/arXiv.2609.36537 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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