Abstract
We propose a framework for resilient autonomous navigation in perceptually challenging unknown environments with mobility-stressing elements such as uneven surfaces with rocks and boulders, steep slopes, negative obstacles like cliffs and holes, and narrow passages. Environments are GPS-denied and perceptually-degraded with variable lighting from dark to lit and obscurants (dust, fog, smoke). Lack of prior maps and degraded communication eliminates the possibility of prior or off-board computation or operator intervention. This necessitates real-time on-board computation using noisy sensor data. To address these challenges, we propose a resilient architecture that exploits redundancy and heterogeneity in sensing modalities. Further resilience is achieved by triggering recovery behaviors upon failure. We propose a fast settling algorithm to generate robust multi-fidelity traversability estimates in real-time. The proposed approach was deployed on multiple physical systems including skid-steer and tracked robots, a high-speed RC car and legged robots, as a part of Team CoSTAR’s effort to the DARPA Subterranean Challenge, where the team won 2nd and 1st place in the Tunnel and Urban Circuits, respectively.
R. Thakker, N. Alatur, D.D. Fan and J. Tordesillas—Equally contributed.
N. Alatur and J. Tordesillas—Work done while at the JPL, Caltech.
©2020, California Institute of Technology. All Rights Reserved.
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Acknowledgements
The authors would like to thank Anushri Dixit and Joel Burdick for support with the Ackermann robot and members of Team CoSTAR for their hardware and testing support. The work is partially supported by the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration (80NM0018D0004), and Defense Advanced Research Projects Agency (DARPA).
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Thakker, R. et al. (2021). Autonomous Off-Road Navigation over Extreme Terrains with Perceptually-Challenging Conditions. In: Siciliano, B., Laschi, C., Khatib, O. (eds) Experimental Robotics. ISER 2020. Springer Proceedings in Advanced Robotics, vol 19. Springer, Cham. https://doi.org/10.1007/978-3-030-71151-1_15
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