Air Ground

Air-ground robotic collaboration focuses on integrating aerial and ground robots for enhanced perception, navigation, and task execution in complex environments. Current research emphasizes developing robust frameworks for information sharing and collaborative planning, often utilizing semantic mapping and algorithms like Generalized Partial Global Planning to coordinate heterogeneous teams. This interdisciplinary field is advancing autonomous systems capabilities, with applications ranging from construction automation to large-scale mapping and search-and-rescue operations in GPS-denied areas. The development of comprehensive real-world datasets is crucial for further progress in multi-robot collaborative perception.