On the journey to enable robots to interact with the real world where humans, animals, and unpredictable elements are acting as independent agents; it is crucial for robots to have the capability to detect dynamic objects. In this paper, we argue that the detection of dynamic objects can be solved by computing the spatiotemporal normals of a point cloud. In our experiments, we demonstrate that this simple method can be used robustly for LiDAR and depth cameras with performances similar to the state of the art while offering a significantly simpler method.

翻译：在实现机器人与真实世界交互的进程中，人类、动物以及其他不可预测元素作为独立主体活动，因此机器人必须具备检测动态物体的能力。本文提出，可通过计算点云的时空法线来解决动态物体检测问题。实验表明，这种简洁方法能稳健应用于激光雷达与深度相机，在性能达到现有技术水平的同时，提供了显著简化的方案。