Coverage Control

Coverage control, encompassing both static and dynamic deployment of agents (robots, sensors, etc.), aims to optimize the monitoring or exploration of a given area. Current research emphasizes decentralized and distributed algorithms, often incorporating machine learning techniques like deep active learning, Gaussian processes, and reinforcement learning, to handle uncertainty and adapt to dynamic environments. These advancements are improving efficiency and robustness in applications ranging from environmental monitoring and search-and-rescue to precision agriculture and infrastructure-free target tracking, impacting fields like robotics, computer vision, and distributed systems.