Heterogeneous UAV

Heterogeneous unmanned aerial vehicle (UAV) systems leverage the complementary capabilities of diverse UAV types (e.g., those equipped with LiDAR versus cameras) to achieve complex tasks more efficiently than homogeneous fleets. Current research emphasizes developing decentralized control algorithms, such as those based on multi-agent reinforcement learning or guiding vector fields, to coordinate these heterogeneous teams for applications like 3D mapping, environmental inspection, and wildfire mitigation. This research area is significant because it enables more robust, adaptable, and cost-effective solutions for a wide range of applications, from infrastructure monitoring to search and rescue operations.