Skip to Main Content
This work is concerned with mapping of indoor environment by a team of robots who share the information they gather to build a global representation of the environment in a consistent, efficient, and scalable way. The well known approach of Decentralized Data Fusion is applied to a widely used representation of Certainty Grid maps. The result is a scalable and intuitive algorithm for combining observations from multiple heterogeneous sensing platforms with built-in processing and communication capabilities. The platforms are assumed to have access to external localization. Results of realistic simulations are presented.