Reactive Navigation

Reactive navigation focuses on enabling robots, particularly UAVs and ground robots, to safely and efficiently navigate dynamic, unknown environments in real-time. Current research emphasizes developing computationally efficient algorithms, such as model predictive control (MPC) and reinforcement learning (RL), often incorporating sensor data from LiDAR or ultrasonic sensors to generate obstacle avoidance maneuvers. These advancements are crucial for deploying autonomous systems in cost-sensitive applications, improving robustness and reducing reliance on computationally expensive techniques like SLAM.