Fast Estimation of Relative Transformation Based on Fusion of Odometry and UWB Ranging Data
<|reference_start|>Fast Estimation of Relative Transformation Based on Fusion of Odometry and UWB Ranging Data: In this paper, we investigate the problem of estimating the 4-DOF (three-dimensional position and orientation) robot-robot relative frame transformation using odometers and distance measurements between robots. Firstly, we apply a two-step estimation method based on maximum likelihood estimation. Specifically, a good initial value is obtained through unconstrained least squares and projection, followed by a more accurate estimate achieved through one-step Gauss-Newton iteration. Additionally, the optimal installation positions of Ultra-Wideband (UWB) are provided, and the minimum operating time under different quantities of UWB devices is determined. Simulation demonstrates that the two-step approach offers faster computation with guaranteed accuracy while effectively addressing the relative transformation estimation problem within limited space constraints. Furthermore, this method can be applied to real-time relative transformation estimation when a specific number of UWB devices are installed.<|reference_end|>
@article{fu2024fast,
    title={Fast Estimation of Relative Transformation Based on Fusion of Odometry
  and UWB Ranging Data},
    author={Yuan Fu, Zheng Zhang, Guangyang Zeng, Chun Liu, Junfeng Wu, Xiaoqiang
  Ren},
    journal={arXiv preprint arXiv:2405.12577},
    year={2024},
    archivePrefix={arXiv},
    eprint={2405.12577},
    primaryClass={cs.RO math.OC}
}