VIR-Swarm: A Distributed and Tightly Integrated Visual-Inertial-UWB System for Anchor Free Swarm Cooperative Localization

ccurate UAV positioning is vital for swarm cooperation. However, this remains challenging in situations where GNSS and other external infrastructures are unavailable. To address the challenge, we propose to only use the onboard MIMU, monocular camera and UWB device to construct a distributed and anchor-free cooperative localization system by tightly fusing the measurements. As the onboard UWB measurements in dynamic motion conditions is noisy and discontinuous, we propose an adaptive adjustment method based on chi-square detection to effectively filter out inconsistent and false ranging information. Moreover, we introduce the pose-only theory to model the visual measurement, which improves the efficiency and accuracy for visual-inertial processing. Then a sliding window extend Kalman filter was constructed to fuse all the measurements in a tightly way, which is capable to work under UWB or visual deprived conditions. To overcome the state consistency challenge inherent in the distributed cooperative structure, we propose to not only model the UWB noisy uncertainty but also the neighbor agents position uncertainty into the measurement model. To validate the effectiveness of proposed our methods, we have established both simulation and hardware test platforms. The proposed method is compared with state-of-the-art (SOTA) UAV localization approaches designed for GNSS-challenged environments. Extensive experiments demonstrate that our algorithm achieves superior positioning accuracy and higher computational efficiency. Moreover, even when vision loss causes other methods to fail, our proposed method continues to operate effectively.