论文标题
基于占用网格的反应性计划者
Occupancy Grid Based Reactive Planner
论文作者
论文摘要
本文提出了在不明界定课程中自动赛车的感知和路径规划管道。该管道最初是为2021 EVGrandPrix自治部门创建的，并在2022年的活动中得到了进一步的改进，这两者都导致了第一名。使用简单的基于激光痛的感知管道将馈送到基于占用网格的扩展算法中，我们确定了驱动的目标点。除了使用占用网格算法外，该管道成功实现了可靠和一致的圈，以了解圆锥定义的轨道周围的方式，平均速度为6.85 m/s，距离为6.85 m/s，总圈速度为63.4秒。
This paper proposes a perception and path planning pipeline for autonomous racing in an unknown bounded course. The pipeline was initially created for the 2021 evGrandPrix autonomous division and was further improved for the 2022 event, both of which resulting in first place finishes. Using a simple LiDAR-based perception pipeline feeding into an occupancy grid based expansion algorithm, we determine a goal point to drive. This pipeline successfully achieved reliable and consistent laps in addition with occupancy grid algorithm to know the ways around a cone-defined track with an averaging speeds of 6.85 m/s over a distance 434.2 meters for a total lap time of 63.4 seconds.
