Cooperative Online Scalar Field Mapping

Cooperative online scalar field mapping focuses on enabling multiple robots to collaboratively build and maintain accurate maps of an environment in real-time. Current research emphasizes distributed algorithms, often leveraging neural networks (e.g., neural radiance fields, deep signed distance functions) or Gaussian processes for efficient map representation and fusion, minimizing communication overhead while maintaining accuracy. This field is crucial for advancing autonomous systems in diverse applications, including robotic exploration, autonomous driving, and infrastructure monitoring, by enabling robust and scalable mapping in complex and dynamic environments.