Collective Perception

Collective perception research focuses on enabling multiple agents (robots, vehicles, or even humans) to collaboratively build a shared understanding of their environment, surpassing the limitations of individual sensors or perspectives. Current research emphasizes developing efficient fusion algorithms, such as multi-resolution voxel grid fusion for LiDAR data and agent-based learning frameworks, to integrate diverse sensor information and improve accuracy while minimizing computational costs. This field is crucial for advancing autonomous driving, multi-robot systems, and even understanding human social perception, with applications ranging from safer autonomous vehicles to more robust and efficient robotic swarms.