The automatic road roller, as a popular type of construction robot, has attracted much interest from both the industry and the research community in recent years. However, when it comes to tunnels where the degeneration issues are prone to happen, it is still a challenging problem to provide an accurate positioning result for the robot. In this paper, we aim to deal with this problem by fusing LiDAR and UWB measurements based on optimization. In the proposed localization method, the directions of non-degeneration will be constrained and the covariance of UWB reconstruction will be introduced to improve the accuracy of localization. Apart from these, a method that can extract the feature of the inner wall of tunnels to assist positioning is also presented in this paper. To evaluate the effectiveness of the proposed method, three experiments with real road roller were carried out and the results show that our method can achieve better performance than the existing methods and can be applied to automatic road roller working inside tunnels. Finally, we discuss the feasibility of deploying the system in real applications and make several recommendations.

翻译：近年来,自动滚轮作为一种受欢迎的建筑机器人,吸引了业界和研究界的极大兴趣,然而,当涉及容易发生退化问题的隧道时,为机器人提供准确定位结果仍是一个具有挑战性的问题。在本文件中,我们的目标是通过在优化的基础上将LiDAR和UWB测量结果引信化来解决这一问题。在拟议的地方化方法中,非退化方向将受到限制,将引入世界银行重建的常态,以提高地方化的准确性。除此之外,本文件还介绍了一种能够提取隧道内部墙特征以协助定位的方法。为了评估拟议方法的有效性,进行了三次真正的滚动试验,结果显示,我们的方法能够比现有方法取得更好的效果,并可用于隧道内自动滚动工程。最后,我们讨论了在实际应用中部署系统的可行性,并提出若干建议。