Mapless Navigation

Mapless navigation focuses on enabling robots to navigate without relying on pre-existing maps, aiming to achieve robust and efficient path planning in dynamic or unknown environments. Current research heavily utilizes deep reinforcement learning (DRL), employing architectures like actor-critic networks and incorporating techniques such as curriculum learning and delayed policy updates to improve generalization and safety. This field is significant for advancing autonomous robotics, particularly in applications like planetary exploration, search and rescue, and warehouse automation, where creating and maintaining accurate maps is challenging or impossible.