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一个两阶段的多目标轨迹优化方案,用于多UGV在视野的急救场景的第一援助场景
IEEE transactions on cybernetics
|March 11, 2024
概括
本研究引入了一种新的两阶段策略,用于优化紧急急救场景中多个无人地面车辆 (多个UGV) 的交付路线,大大减少关键任务的计算时间.
科学领域:
- 机器人和自动化机器人与自动化
- 运营研究 运营研究
- 应急响应系统 应急响应系统
背景情况:
- 及时提供急救物资对于在大规模事故中拯救生命至关重要.
- 无人地面车辆 (UGV) 为紧急物流提供了一个有前途的解决方案.
- 对于复杂事故场景中的多重UGV,现有的轨迹优化方法是不够的.
研究的目的:
- 为应对大规模事故中多个UGV的轨迹优化挑战,提供急救服务.
- 制定一个高效和有效的多UGV轨道规划策略.
- 为了在时间敏感的急救任务中减少最佳轨迹解决方案的计算时间.
主要方法:
- 一个两阶段的,完全解模糊的多目标优化策略.
- 时间尺度涉及三维道无碰撞轨迹 (TITTCT) 算法,用于生成无碰撞的粗道.
- 模糊的多目标转录方法用于解决与优先级约束脱的最佳控制问题.
主要成果:
- 显著减少了多个UGV轨迹规划的计算时间.
- 在定义的配置空间内成功生成无碰撞轨迹.
- 优化多个目标,包括通过模拟和实验验证实的愿望水平.
结论:
- 拟议的两阶段模糊优化策略有效优化了多UGV轨迹的急救交付.
- TITTCT算法和模糊转录方法提高了计算性能,这对于应急响应至关重要.
- 该方法在现实应用中展示了实际有效性和增强的计算效率.
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