García Daza Iván, Rentero Mónica, Salinas Maldonado Carlota, Izquierdo Gonzalo Ruben, Hernández Parra Noelia, Ballardini Augusto, Fernandez Llorca David
Computer Engineering Department, Universidad de Alcalá, 28805 Alcalá de Henares, Spain.
Sensors (Basel). 2020 Jul 23;20(15):4097. doi: 10.3390/s20154097.
Autonomous driving systems are set to become a reality in transport systems and, so, maximum acceptance is being sought among users. Currently, the most advanced architectures require driver intervention when functional system failures or critical sensor operations take place, presenting problems related to driver state, distractions, fatigue, and other factors that prevent safe control. Therefore, this work presents a redundant, accurate, robust, and scalable LiDAR odometry system with fail-aware system features that can allow other systems to perform a safe stop manoeuvre without driver mediation. All odometry systems have drift error, making it difficult to use them for localisation tasks over extended periods. For this reason, the paper presents an accurate LiDAR odometry system with a fail-aware indicator. This indicator estimates a time window in which the system manages the localisation tasks appropriately. The odometry error is minimised by applying a dynamic 6-DoF model and fusing measures based on the Iterative Closest Points (ICP), environment feature extraction, and Singular Value Decomposition (SVD) methods. The obtained results are promising for two reasons: First, in the KITTI odometry data set, the ranking achieved by the proposed method is twelfth, considering only LiDAR-based methods, where its translation and rotation errors are 1.00 % and 0.0041 deg/m, respectively. Second, the encouraging results of the fail-aware indicator demonstrate the safety of the proposed LiDAR odometry system. The results depict that, in order to achieve an accurate odometry system, complex models and measurement fusion techniques must be used to improve its behaviour. Furthermore, if an odometry system is to be used for redundant localisation features, it must integrate a fail-aware indicator for use in a safe manner.
自动驾驶系统即将在交通系统中成为现实，因此，正在寻求用户的最大程度接受。目前，最先进的架构在功能系统故障或关键传感器操作发生时需要驾驶员干预，这带来了与驾驶员状态、分心、疲劳以及其他妨碍安全控制的因素相关的问题。因此，这项工作提出了一种具有故障感知系统功能的冗余、准确、稳健且可扩展的激光雷达里程计系统，该系统可以允许其他系统在无需驾驶员干预的情况下执行安全停车操作。所有里程计系统都存在漂移误差，这使得长时间将它们用于定位任务变得困难。出于这个原因，本文提出了一种带有故障感知指示器的精确激光雷达里程计系统。该指示器估计系统能够适当管理定位任务的时间窗口。通过应用动态6自由度模型并融合基于迭代最近点（ICP）、环境特征提取和奇异值分解（SVD）方法的测量值，里程计误差被最小化。所获得的结果很有前景，原因有两个：第一，在KITTI里程计数据集中，仅考虑基于激光雷达的方法时，所提出方法的排名为第十二，其平移误差和旋转误差分别为1.00%和0.0041度/米。第二，故障感知指示器的令人鼓舞的结果证明了所提出的激光雷达里程计系统的安全性。结果表明，为了实现精确的里程计系统，必须使用复杂的模型和测量融合技术来改善其性能。此外，如果里程计系统要用于冗余定位功能，则必须集成一个故障感知指示器以便安全使用。
