In auto-parking systems, a certain degree of error in the path tracking algorithm is inevitable. This is caused by actuator error, tire slipping, or other factors relevant to and included in the parking process. In such situations, the parking path needs to be updated to finish parking successfully which is referred to as secondary path planning. Herein, a new geometry-based method is proposed to deal with this issue, which can be called the pattern-based method. In this method, a predefined path pattern set consisting of 24 multi-segment patterns is developed first. These patterns are composed of straight lines and arcs and account for constraints due to motion and the immediate environment. Then, a traversal policy is adopted to select the path pattern from the set, and the sequential quadratic programming algorithm is used to determine the optimal parameters that fine-tune the pattern to meet the current constraints. In the simulation section, the effectiveness of the proposed method is demonstrated. Moreover, compared to the search-based method represented by a variation of rapidly exploring random tree*, the proposed method has a higher planning performance.

中文翻译：

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一种新的基于几何的自动停车辅助路径规划

在自动泊车系统中，路径跟踪算法存在一定程度的误差是不可避免的。这是由执行器错误、轮胎打滑或与停车过程相关并包含在其中的其他因素引起的。在这种情况下，需要更新停车路径以成功完成停车，这称为二次路径规划。在此，提出了一种新的基于几何的方法来解决这个问题，称为基于模式的方法。在该方法中，首先开发由 24 个多段模式组成的预定义路径模式集。这些图案由直线和弧线组成，并考虑了由于运动和直接环境造成的约束。然后，采用遍历策略从集合中选择路径模式，并且使用顺序二次规划算法来确定微调模式以满足当前约束的最佳参数。在仿真部分，证明了所提出方法的有效性。此外，与以快速探索随机树*为代表的基于搜索的方法相比，所提出的方法具有更高的规划性能。