RONov 11, 2021

Autonomous Teamed Exploration of Subterranean Environments using Legged and Aerial Robots

arXiv:2111.06482v2108 citations
Originality Incremental advance
AI Analysis

This addresses the problem of exploring complex, large-scale subterranean settings like caves and mines for applications in search and rescue or mapping, representing an incremental advance in multi-robot coordination.

The paper tackles autonomous exploration of subterranean environments by developing a strategy using legged and aerial robots, verified through a 45-minute field deployment in an underground mine and simulations.

This paper presents a novel strategy for autonomous teamed exploration of subterranean environments using legged and aerial robots. Tailored to the fact that subterranean settings, such as cave networks and underground mines, often involve complex, large-scale and multi-branched topologies, while wireless communication within them can be particularly challenging, this work is structured around the synergy of an onboard exploration path planner that allows for resilient long-term autonomy, and a multi-robot coordination framework. The onboard path planner is unified across legged and flying robots and enables navigation in environments with steep slopes, and diverse geometries. When a communication link is available, each robot of the team shares submaps to a centralized location where a multi-robot coordination framework identifies global frontiers of the exploration space to inform each system about where it should re-position to best continue its mission. The strategy is verified through a field deployment inside an underground mine in Switzerland using a legged and a flying robot collectively exploring for 45 min, as well as a longer simulation study with three systems.

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