Dynamic Occupancy Grid Mapping is a technique used to generate a local map of the environment containing both static and dynamic information. Typically, these maps are primarily generated using lidar measurements. However, with improvements in radar sensing, resulting in better accuracy and higher resolution, radar is emerging as a viable alternative to lidar as the primary sensor for mapping. In this paper, we propose a radar-centric dynamic occupancy grid mapping algorithm with adaptations to the state computation, inverse sensor model, and field-of-view computation tailored to the specifics of radar measurements. We extensively evaluate our approach using real data to demonstrate its effectiveness and establish the first benchmark for radar-based dynamic occupancy grid mapping using the publicly available Radarscenes dataset.

翻译：动态占据网格建图是一种生成包含静态与动态信息的局部环境地图的技术。传统上，这类地图主要利用激光雷达测量数据生成。然而，随着雷达感知技术在精度与分辨率上的显著提升，其正逐步成为替代激光雷达的主要建图传感器。本文提出了一种以雷达为核心的动态占据网格建图算法，针对雷达测量的特性，对状态计算、逆传感器模型及视场角计算进行了定制化改进。我们通过真实数据对所提方法进行了全面评估，验证其有效性，并基于公开的Radarscenes数据集建立了首个雷达动态占据网格建图基准。