# Continuous-Time Ultra-Wideband-Inertial Fusion

arXiv: https://arxiv.org/abs/2301.09033 · HTML: https://mlsanity.com/paper/2301.09033/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 22 Jan 2023.

## Built on by (most cited first, 1 of 1)

- [ULOC: Learning to Localize in Complex Large-Scale Environments with Ultra-Wideband Ranges](https://mlsanity.com/paper/2409.11122/) (2024)

## Abstract (arXiv)

We introduce a novel framework of continuous-time ultra-wideband-inertial sensor fusion for online motion estimation. Quaternion-based cubic cumulative B-splines are exploited for parameterizing motion states continuously over time. Systematic derivations of analytic kinematic interpolations and spatial differentiations are further provided. Based thereon, a new sliding-window spline fitting scheme is established for asynchronous multi-sensor fusion and online calibration. We conduct a dedicated validation of the quaternion spline fitting method, and evaluate the proposed system, SFUISE (spline fusion-based ultra-wideband-inertial state estimation), in real-world scenarios using public data set and experiments. The proposed sensor fusion system 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 at https://github.com/KIT-ISAS/SFUISE.