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

Dynamic Object Detection in Range data using Spatiotemporal Normals