Planning Paths through Occlusions in Urban EnvironmentsDownload PDF

16 Jun 2022, 10:45 (modified: 14 Nov 2022, 17:52)CoRL 2022 OralReaders: Everyone
Student First Author: no
Keywords: Navigation, Occluded Environments, Semantic Scene Understanding
TL;DR: Planning through occluded urban environments using image inpainting techniques.
Abstract: This paper presents a novel framework for planning in unknown and occluded urban spaces. We specifically focus on turns and intersections where occlusions significantly impact navigability. Our approach uses an inpainting model to fill in a sparse, occluded, semantic lidar point cloud and plans dynamically feasible paths for a vehicle to traverse through the open and inpainted spaces. We demonstrate our approach using a car’s lidar data with real-time occlusions, and show that by inpainting occluded areas, we can plan longer paths, with more turn options compared to without inpainting; in addition, our approach more closely follows paths derived from a planner with no occlusions (called the ground truth) compared to other state of the art approaches.
Supplementary Material: zip
Code: https://github.com/genplanning/generative_planning
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