Ruslan Agishev presents Trajectory Optimization Using Learned Robot-Terrain Interaction Model in Exploration of Large Subter

On 2022-05-19 - 2022-05-19 11:00:00 at G205, Karlovo náměstí 13, Praha 2
We consider the task of active exploration of large subterranean environments
with a ground mobile robot. Our goal is to autonomously explore a large unknown
area and to obtain an accurate coverage and localization of objects of interest
(artefacts). The exploration is constrained by the restricted operation time in
rescue scenarios, as well as a hard rough terrain. To this end, we introduce a
novel optimization strategy that respects these constraints by maximizing the
environment coverage by onboard sensors while producing feasible trajectories
with the help of a learned robot-terrain interaction model. The approach is
evaluated in diverse subterranean simulated environments, showing the viability
of traversability-aware exploration in challenging scenarios. In addition, we
demonstrate that the local trajectory optimization improves the global coverage
of an environment as well as the overall object detection results.
Responsible person: Petr Pošík