Planning Paths through Occlusions in Urban Environments

2022/12/29 by Yutao Han, Youya Xia, Han, Yutao +5 · 1 citation
Computer Science · Engineering · Environmental Science · #Autonomous Vehicle Technology and Safety #FOS: Computer and information sciences #Remote Sensing and LiDAR Applications #Robotics (cs.RO) #Video Surveillance and Tracking Methods

paper · pdf · doi:10.48550/arxiv.2212.14138

openalex publication_date 2022/12/29 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

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.

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