无人机的轨迹规划器基于由动力学基因调节网络获得的潜在场
Juncao Hong1, Diquan Chen1, Wenji Li1,2,3
1College of Engineering, Shantou University, Shantou 515063, China.
Sensors (Basel, Switzerland)
|September 28, 2023
概括
这项研究介绍了一种用于四旋翼无人机的新型轨迹规划器,利用动力学基因调节网络潜力场. 这种方法通过将环境数据与无人机动态相结合,提高了复杂环境中的飞行安全和效率.
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 控制系统
背景情况:
- 由于复杂的环境和动态限制,四旋翼无人机在现实应用中面临着重大挑战.
- 有效的轨道规划对于确保无人机操作的安全和效率至关重要.
研究的目的:
- 开发一种创新的四旋翼飞行轨迹计划器,将环境感知与无人机的动态状态相结合.
- 通过将动力学约束纳入潜在的现场框架,解决现有方法的局限性.
主要方法:
- 开发了一种新的动力学基因调节网络 (K-GRN) 潜力场.
- K-GRN潜力场增强了基因调节网络 (GRN) 模型对无人机动态和环境环境的适应性.
- 轨迹规划器利用这个K-GRN生成安全和高效的飞行路径.
主要成果:
- 拟议的轨迹规划器成功引导四旋翼无人机通过复杂的环境.
- 生成的轨迹有效考虑动态约束,提高适应性和稳定性.
- 经验结果证明了该方法的有效性.
结论:
- K-GRN潜力场方法为四旋翼飞行轨迹规划提供了一个强大的解决方案.
- 这种方法可以在复杂和动态的场景中提高无人机性能.
- 环境洞察力和动力学约束的整合导致了优越的轨迹生成.
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