2024
Learning Self-Supervised Traversability With Navigation Experiences of Mobile Robots: A Risk-Aware Self-Training Approach
RA-L 2024
Mobile robots operating in outdoor environments face the challenge of navigating various terrains with different degrees of difficulty. Therefore, traversability estimation is crucial for safe and efficient robot navigation. Current approaches utilize a robot's driving experience to learn traversabi