Obstacle detection is one of the basic tasks of a robot movement in an unknown environment. The use of a LiDAR (Light Detection And Ranging) sensor allows one to obtain a point cloud in the vicinity of the sensor. After processing this data, obstacles can be found and recorded on a map. For this task, I present a pipeline capable of detecting obstacles even on a computationally limited device. The pipeline was also tested on a real robot and qualitatively evaluated on a dataset, which was collected in Brno University of Technology lab. Time consumption was recorded and compared with 3D object detectors.

翻译：障碍物检测是机器人在未知环境中运动的基本任务之一。使用LiDAR（激光探测与测距）传感器可获取传感器周围环境的点云数据。通过对这些数据进行处理，可以识别并在地图中记录障碍物信息。本文提出了一种能够在计算能力有限的设备上实现障碍物检测的处理流程。该流程已在真实机器人上进行了测试，并在布尔诺理工大学实验室采集的数据集上进行了定性评估。同时记录了时间消耗，并与3D目标检测器进行了对比分析。