This paper presents a Lidar/ultra-wideband (UWB) fusion algorithm for simultaneous localization and mapping (SLAM) with anti-degeneration capability. In the proposed algorithm, the sensor states are estimated by minimizing the sum of the Mahalanobis norm of all measurement residuals associated with the Lidar sensor and the UWB sensors. Additionally, considering that a poor geometric distribution of the sensor measurements will introduce large estimation uncertainties in the fusion algorithm, a trade-off parameter with its self-adjustment strategy is introduced in the fusion algorithm to adjust the ratio of the contributions provided by the Lidar measurement residuals and the UWB measurement residuals in the state estimation according to their degeneration degrees. A method that can detect and determine the degeneration degree of the sensor measurements is also presented in the paper. In order to evaluate the performance of the proposed fusion algorithm, two experiments were carried out. Results of the experiments show that the proposed Lidar/UWB fusion algorithm can automatically adjust the trade-off parameter according to the degeneration degrees of the sensor measurements and mitigate the effects of the degeneration.

中文翻译：

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基于Lidar / UWB Fusion的具有抗变性能力的SLAM

本文提出了一种具有抗变性能力的同时定位和制图（SLAM）的激光雷达/超宽带（UWB）融合算法。在所提出的算法中，通过最小化与激光雷达传感器和超宽带传感器相关联的所有测量残差的马哈拉诺比斯范数之和来估计传感器状态。另外，考虑到传感器测量值的不良几何分布会在融合算法中引入较大的估计不确定性，因此在融合算法中引入了具有自调整策略的折衷参数，以调整激光雷达提供的贡献比率状态估计中的测量残差和UWB测量残差根据其退化程度进行估计。本文还提出了一种可以检测并确定传感器测量值退化程度的方法。为了评估所提出的融合算法的性能，进行了两个实验。实验结果表明，所提出的激光雷达/超宽带融合算法能够根据传感器测量的退化程度自动调整权衡参数，减轻退化的影响。