基于相对距离限制的异质空地机器人适应性合作定位方法,在无卫星环境中使用
Shidong Han1,2, Zhi Xiong1, Chenfa Shi1
1Navigation Research Center, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China.
Sensors (Basel, Switzerland)
|July 27, 2024
概括
这项研究引入了空对地面机器人的自适应合作本地化方法,即使使用有限数量的已知的无人机 (UAV),也提高了准确性. 这种方法确保了在没有卫星的环境中强大的机器人导航.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 导航系统 导航系统
- 人工智能的人工智能
背景情况:
- 合作本地化 (CL) 对于无卫星环境中的空中地面机器人至关重要.
- 传统的CL方法需要最小数量的已知位置的无人机 (UAV),当这个数量不足时,限制了应用.
- 现有的方法与动态变化的网络拓和不同数量的参考节点作斗争.
研究的目的:
- 为空地机器人提出一种新的适应性CL方法,克服传统方法的局限性.
- 开发一种与动态变化的已知位置无人机数量有效运行的方法.
- 提高无人地面车辆 (UGV) 合作本地化的精度和稳定性.
主要方法:
- 提出了一个基于相对距离约束的自适应性CL方法.
- 根据已知位置的无人机的数量动态设置了自适应融合估计值.
- 对于众所周知的无人机,使用无人机和UGV之间的最佳空间几何配置.
- 当已知的无人机稀缺时,相对距离观测和INS数据使用历史和当前约束来融合.
主要成果:
- 拟议的方法通过使用可变数量的已知位置无人机实现了自适应的核聚变估计.
- 实验结果证明了自适应性CL方法的有效性.
- 用于UGV的高精度CL解决方案在不同的网络条件下实现.
结论:
- 新的自适应性CL方法为在具有挑战性的环境中空对地机器人导航提供了强大的解决方案.
- 该方法有效地处理了参考无人机数量不足或动态变化的场景.
- 这项研究有助于改善异质机器人团队的自主导航能力.
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