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相关概念视频

Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

101
Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence...
101

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相关实验视频

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Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
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一个新的多目标虫优化器用于多UAV合作路径规划.

Qianwen Shen1, Damin Zhang1, Qing He1

  • 1School of Big Data and Information Engineering, Guizhou University, Guiyang, 550000, People's Republic of China.

Heliyon
|September 19, 2024
PubMed
概括

一个新的算法,DENSDBO-ASR,通过平衡融合和多样性来增强多个无人机 (UAV) 路径规划. 这种方法有效地处理合作无人机操作的复杂约束.

科学领域:

  • 机器人和自动化机器人与自动化
  • 人工智能的人工智能
  • 运营研究 运营研究

背景情况:

  • 多个无人机 (UAV) 路径规划对于协作任务至关重要.
  • 传统的方法与融合,多样性和约束处理作斗争.
  • 复杂的多目标优化是协作无人机路径规划固有的.

研究的目的:

  • 为多个无人机路径规划开发一个先进的算法.
  • 解决现有方法在趋同,多样性和约束管理方面的局限性.
  • 优化协作路径规划,考虑多个目标.

主要方法:

  • 引入了一个具有自适应性随机排名 (DENSDBO-ASR) 的定向进化非主导排序虫优化器.
  • 制定了两个目标:总成本 (长度,高度) 和总成本 (威胁,时间).
  • 集成的定向突变和交叉用于增强的融合和全球搜索,以及适应性随机排名用于约束处理.

主要成果:

  • 与其他五种算法相比,DENSDBO-ASR在趋同准确度和人口多样性方面表现出卓越的表现.
  • 在具有挑战性的场景中成功确定了可行的路径,实现了低的目标函数值 (例如637.26和0).
  • 通过受约束问题函数 (CF) 测试,威尔科克森等级总和测试和弗里德曼测试验证的有效性.
关键词:
适应性随机排名机制 适应性随机排名机制合作路径规划合作路径规划方向性进化战略的方向性进化战略多个无人机的无人机.

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结论:

  • DENSDBO-ASR为多个无人机路径规划挑战提供了一种特殊的优化方法.
  • 该算法有效地平衡了融合和多样性,同时管理复杂的约束.
  • 经过验证的优越性使得DENSDBO-ASR成为协作机器人操作的宝贵工具.