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用机器人控制蚊子的覆盖路径规划

Ash Yaw Sang Wan1, Prabakaran Veerajagadheswar1, Mohan Rajesh Elara1

  • 1ROAR Lab, Engineering Product Development, Singapore University of Technology and Design, Singapore, 487372, Singapore.

Scientific reports
|August 23, 2025
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概括
此摘要是机器生成的。

自动化蚊子控制的新方法优先考虑人类活动以有效地覆盖区域. 这种方法有助于捕捉蚊子并减少疾病的传播.

关键词:
自动化蚊子控制生物启发的神经网络覆盖路径的规划人类活动意识捕捉蚊子的机器人

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科学领域:

  • 机器人和人工智能
  • 害虫防治技术
  • 公共卫生

背景情况:

  • 自动化蚊子控制对于减轻媒介性疾病至关重要.
  • 现有的机器人解决方案难以有效覆盖区域,
  • 需要敏感的策略来优先考虑人类活动模式.

研究的目的:

  • 提出一个全覆盖路径规划 (HFA-CCPP) 的新型人为优先方法,用于自动化控制蚊子.
  • 将Glasius生物启发的神经网络 (GBNN) 与人类活动模式相结合,以系统地覆盖区域.
  • 通过捕捉蚊子的机器人Dragonfly来证明HFA-CCPP的有效性.

主要方法:

  • 完整覆盖路径规划 (HFA-CCPP) 的人类优先方法的开发.
  • 利用Glasius生物启发的神经网络 (GBNN) 模拟和考虑人类活动模式.
  • 在模拟和现实环境中对HFA-CCPP与传统GBNN进行比较分析.

主要成果:

  • 与传统的GBNN相比,HFA-CCPP的覆盖面效率更高.
  • 提出的方法实现了覆盖高人类活动地区的最小时间.
  • 在HFA-CCPP方法中观察到蚊子捕获效率提高.

结论:

  • 在自动化蚊子控制策略方面,HFA-CCPP具有显著的进步.
  • 人类活动模式的优先考虑导致了更高效和有效的蚊子种群管理.
  • 这种方法在减少媒介传播疾病的发生方面具有很大的潜力.