Autonomous Navigation

Autonomous navigation research aims to enable robots and vehicles to navigate complex environments without human intervention, focusing on safe and efficient path planning and execution. Current efforts concentrate on improving perception through sensor fusion (e.g., LiDAR, cameras, sonar) and leveraging machine learning techniques, particularly deep reinforcement learning and neural networks, for decision-making and control, often incorporating prior maps or learned models of environment dynamics. This field is crucial for advancing robotics, autonomous driving, and space exploration, with applications ranging from warehouse logistics and agricultural automation to underwater exploration and planetary landing.