Learning Spatiotemporal Occupancy Grid Maps for Lifelong Navigation in Dynamic Scenes
Hugues Thomas,Matthieu Gallet de Saint Aurin,Jian Zhang,Timothy D. Barfoot,Hugues Thomas,Matthieu Gallet de Saint Aurin,Jian Zhang,Timothy D. Barfoot
We present a novel method for generating, predicting, and using Spatiotemporal Occupancy Grid Maps (SOGM), which embed future information of dynamic scenes. Our au-tomated generation process creates groundtruth SOGMs from previous navigation data. We build on prior work to annotate lidar points based on their dynamic properties, which are then projected on time-stamped 2D grids: SOGMs. We design a...
