Abstract
In this paper, we report on the developed system for assessment of ground unit terrain traversal cost using aerial reconnaissance of the expected mission environment. The system combines an aerial vehicle with ground robot terrain learning in the traversal cost modeling utilized in the mission planning for ground units. The aerial vehicle is deployed to capture visual data used to build a terrain model that is then used for the extraction of the terrain features of the expected operational area of the ground units. Based on the previous traversal experience of the ground units in similar environments, the learned model of the traversal cost is employed to predict the traversal cost of the new expected operational area to plan a cost-efficient path to visit the desired locations of interest. The particular modules of the system are demonstrated in an experimental scenario combining the deployment of an unmanned aerial vehicle with a multi-legged walking robot used for learning the traversal cost model.
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Acknowledgement
The presented work has been supported under the OP VVV funded project CZ.02.1.01/0.0/0.0/16_019/0000765 “Research Center for Informatics”. The support under grant No. SGS19/176/OHK3/3T/13 to Miloš Prágr and Petr Váňa is also gratefully acknowledged.
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Prágr, M., Váňa, P., Faigl, J. (2020). Aerial Reconnaissance and Ground Robot Terrain Learning in Traversal Cost Assessment. In: Mazal, J., Fagiolini, A., Vasik, P. (eds) Modelling and Simulation for Autonomous Systems. MESAS 2019. Lecture Notes in Computer Science(), vol 11995. Springer, Cham. https://doi.org/10.1007/978-3-030-43890-6_1
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