基于探索的计划,用于多个目标的搜索与现实无人机的结果
Bilal Yousuf1, Zsófia Lendek1, Lucian Buşoniu1
1Department of Automation, Technical University of Cluj-Napoca, Memorandumului 28, 400114 Cluj-Napoca, Romania.
Sensors (Basel, Switzerland)
|May 11, 2024
概括
这项研究介绍了一种新的无人机搜索策略,使用回退视界规划器来有效地定位静态目标. 该方法在模拟和现实世界的实验中优于基线方法.
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
- 计算机视觉 计算机视觉
背景情况:
- 无人机越来越多地用于搜索和监视任务.
- 在无人机操作中,有效地定位未知的静态目标是一个重大挑战.
- 现有的方法,如草机和积极搜索模式都有局限性.
研究的目的:
- 开发和评估一种新的,高效的无人机搜索策略,用于定位未知数量的静态目标.
- 将勘探和目标精细化结合在一个回落的地平线规划框架中.
- 与基线方法相比,证明拟议方法的有效性.
主要方法:
- 使用多目标颗粒过器,根据不完美的测量更新目标强度.
- 实施一个回落的地平线规划器,优化无人机运动的探索和改进.
- 集成一个避障控制器用于路点导航.
- 通过模拟和现实世界实验验验证这种方法,使用Parrot Mambo无人机.
主要成果:
- 与草机和主动搜索基线相比,提出的回退视界规划器显著提高了搜索效率.
- 该系统成功地使用车载图像细分来定位目标进行测量.
- 该框架在模拟环境和现实环境中表现出强的性能.
- 自信地定位的目标被动态地从搜索空间中移除.
结论:
- 新的回落地平线规划框架为基于无人机的静态目标搜索和定位提供了一种优越的方法.
- 整合多目标颗粒过和勘探-精炼目标提高了搜索效率.
- 在现实世界的实验中取得的成功表明了拟议方法的实际应用性.
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