Continuous-Time Ultra-Wideband-Inertial Fusion

01/22/2023

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by   Kailai Li, et al.

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We present a novel continuous-time online state estimation framework using ultra-wideband and inertial sensors. For representing motion states continuously over time, quaternion-based cubic B-splines are exploited with efficient solutions to kinematic interpolations and spatial differentiations. Based thereon, a sliding-window spline fitting scheme is established for asynchronous multi-sensor fusion and online calibration. We evaluate the proposed system, SFUISE (spline fusion-based ultra-wideband-inertial state estimation), in real-world scenarios based on public data set and experiments. The proposed spline fusion scheme is real-time capable and delivers superior performance over state-of-the-art discrete-time schemes. We release the source code and own experimental data set at https://github.com/KIT-ISAS/SFUISE.