Deep Reinforcement Learning for Dynamic Obstacle Avoidance of Mobile Robots in Indoor Environments: A Review
Highlights What are the main findings? Systematically classifies DRL algorithms for indoor mobile robot dynamic obstacle avoidance. Analyzes core challenges and improved strategies across five key technical dimensions. What are the implications of the main findings? Provides a unified reference framework for robot navi...