Abstract
Planetary exploration scenarios illustrate the need for robots that are capable to operate in unknown environments without direct human interaction. Motivated by the DLR SpaceBot Cup 2015, where robots should explore a Mars-like environment, find and transport objects, take a soil sample, and perform assembly tasks, we developed autonomous capabilities for our mobile manipulation robot Momaro. The robot perceives and maps previously unknown, uneven terrain using a 3D laser scanner. We assess drivability and plan navigation for the omnidirectional drive. Using its four legs, Momaro adapts to the slope of the terrain. It perceives objects with cameras, estimates their pose, and manipulates them with its two arms autonomously. For specifying missions, monitoring mission progress, and on-the-fly reconfiguration, we developed suitable operator interfaces. With the developed system, our team NimbRo Explorer solved all tasks of the DLR SpaceBot Camp 2015.
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Schwarz, M., Schüller, S., Lenz, C., Droeschel, D., Behnke, S. (2017). Supervised Autonomy for Exploration and Mobile Manipulation in Rough Terrain. In: Chen, W., Hosoda, K., Menegatti, E., Shimizu, M., Wang, H. (eds) Intelligent Autonomous Systems 14. IAS 2016. Advances in Intelligent Systems and Computing, vol 531. Springer, Cham. https://doi.org/10.1007/978-3-319-48036-7_10
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DOI: https://doi.org/10.1007/978-3-319-48036-7_10
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