论文标题
使用Bernstein多项式在线运动计划，以增强自动驾驶汽车的目标定位
On-line Motion Planning Using Bernstein Polynomials for Enhanced Target Localization in Autonomous Vehicles
论文作者
论文摘要
在现代应用中，使用自动驾驶汽车在目标定位方面强调了它们的出色效率，提高安全性以及比人类操作方法的成本优势。对于本地化任务，可以使用自动驾驶汽车来提高效率并确保目标尽可能快，精确地定位。但是，设计运动计划方案以适合实时实施的计算有效方式实现这些目标并不直接。在本文中，我们引入了一种运动计划解决方案，以增强目标定位，利用Bernstein多项式基础函数来近似目标轨迹的概率分布。这使我们能够得出运动计划者使用的估计性能标准，以增强估计器功效。总而言之，我们提出了验证建议算法的有效性的模拟结果。
The use of autonomous vehicles for target localization in modern applications has emphasized their superior efficiency, improved safety, and cost advantages over human-operated methods. For localization tasks, autonomous vehicles can be used to increase efficiency and ensure that the target is localized as quickly and precisely as possible. However, devising a motion planning scheme to achieve these objectives in a computationally efficient manner suitable for real-time implementation is not straightforward. In this paper, we introduce a motion planning solution for enhanced target localization, leveraging Bernstein polynomial basis functions to approximate the probability distribution of the target's trajectory. This allows us to derive estimation performance criteria which are used by the motion planner to enhance the estimator efficacy. To conclude, we present simulation results that validate the effectiveness of the suggested algorithm.
