Autonomous Exploration Planner

Autonomous exploration planners are algorithms enabling robots to efficiently explore unknown environments, aiming to maximize coverage and minimize redundant travel. Current research focuses on improving efficiency in complex, dynamic settings, often incorporating advanced algorithms like asymmetric traveling salesman problem (ATSP) solutions for path planning and leveraging diverse sensor data (LiDAR, cameras) for informed decision-making. These advancements are crucial for applications ranging from search and rescue in challenging terrains (e.g., subterranean environments) to planetary exploration, improving the speed and robustness of autonomous robotic systems.