A Survey on Reinforcement Learning Applications in SLAM
This survey investigates how Reinforcement Learning (RL) can improve Simultaneous Localization and Mapping (SLAM) for robots. It examines RL's use in path planning, loop closure, exploration, and obstacle detection to enhance navigation skills in complex environments. The study reveals advancements that make robots better at mapping and moving autonomously.