Cooperative Localization
Overview
Cooperative localization studies how multiple agents estimate their positions and orientations by combining their own motion data with observations of one another. Methods include decentralized Kalman filters, factor-graph optimization, consensus and message passing, using measurements such as UWB or acoustic ranges, visual bearings, LiDAR, and inertial data. It supports navigation in GNSS-denied or infrastructure-free settings, from indoor robot teams and aerial formations to underwater vehicles and wearable devices. A central challenge is balancing accuracy and consistency against limited, delayed, or unreliable communication, while weak observability and shared position errors can make relative measurements insufficient without an absolute reference.
Latest papers
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