Avoidance Navigation

Avoidance navigation focuses on enabling autonomous systems, from robots and UAVs to autonomous vehicles and even recommender systems, to safely and efficiently navigate around obstacles and avoid collisions. Current research emphasizes robust and generalizable solutions, employing techniques like deep reinforcement learning with causal feature selection to improve performance in unseen environments, and adaptive potential field methods coupled with optimized path planning algorithms for emergency situations. These advancements are crucial for enhancing the safety and reliability of autonomous systems across various domains, from safer air and sea travel to improved user experience in online information access.