基于基因校正的改进免疫火焰优化,用于自动倒车停车
Gang Liu1,2, Xinli Xu3, Longda Wang4
1College of Engineering, Inner Mongolia Minzu University, Tongliao 028000, China.
Sensors (Basel, Switzerland)
|April 13, 2024
概括
这项研究引入了一种改进的火焰优化算法,以实现更流,更短的自动倒车停车轨迹. 新方法提高了轨迹优化和跟踪控制的准确性,确保更安全的停车机动.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 人工智能的人工智能
- 控制系统工程 控制系统工程
背景情况:
- 在自动倒车停车时实现精确的参考轨迹是具有挑战性的,往往导致碰撞或非最佳路径.
- 现有的方法难以同时优化轨迹的平滑度,长度和泊位角度.
研究的目的:
- 为自动倒车停车系统开发一个优化的参考轨迹.
- 为了提高轨迹的平滑性,减少长度,并最大限度地减少泊位倾斜角度.
- 为了提高避免碰撞和跟踪控制的准确性.
主要方法:
- 开发了一种改进的免疫火焰优化算法,包括基因校正.
- 一个参考轨迹优化模型是使用立方线合和边界交叉解决方案构建的.
- 整合了非线性下降策略和基于融合距离的解决方案集维护机制,以促进全球优化.
主要成果:
- 拟议的算法在参考轨迹优化方面表现出更高的准确性.
- 实现了优化参考轨迹的有效跟踪控制.
- 实验验证是在一个特定的车库地点进行的.
结论:
- 改进的免疫火焰优化方法为自动反向停车轨迹规划提供了卓越的方法.
- 该方法有效地解决了光滑,长度和倾斜角度优化方面的挑战.
- 在轨道优化和跟踪控制中提高准确性有助于更安全,更有效的自动停车.
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