Safe Navigation

Safe navigation research focuses on enabling robots and autonomous systems to move reliably and safely in diverse, often unpredictable environments, prioritizing collision avoidance and socially acceptable behavior. Current efforts concentrate on integrating advanced perception (e.g., LiDAR, vision-language models) with robust control strategies like control barrier functions and reinforcement learning, often incorporating uncertainty estimation and probabilistic methods for improved decision-making. This field is crucial for advancing robotics, autonomous vehicles, and assistive technologies, impacting safety and efficiency in various applications from industrial automation to personal mobility.