[RA-L '24] Learning self-supervised traversability with navigation experiences of mobile robots: A risk-aware self-training approach
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Updated
Sep 16, 2025 - C++
[RA-L '24] Learning self-supervised traversability with navigation experiences of mobile robots: A risk-aware self-training approach
Autonomous hexapod rover using Python Raspberry Pi control, Arduino/C++ sensor firmware, Buehler-clock gait control, and simulation-backed terrain navigation.
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