Uncertainty Aware Navigation

Uncertainty-aware navigation focuses on enabling robots to safely and efficiently navigate environments with incomplete or uncertain information about the terrain, obstacles, or other agents. Current research emphasizes probabilistic models, often leveraging deep learning architectures, to quantify and incorporate uncertainty into path planning algorithms, including dynamic programming and methods based on Markov Decision Processes. This work is crucial for advancing the capabilities of autonomous robots in complex and unpredictable settings, such as planetary exploration, search and rescue, and delivery in crowded urban areas, by improving robustness and safety.