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相关概念视频

Machines: Problem Solving I01:22

Machines: Problem Solving I

A toggle clamp is a mechanical device commonly used for holding and clamping objects in various applications, such as woodworking, metalworking, and assembly operations. Consider a toggle clamp subjected to a force of 200 N at the handle. The vertical clamping force can be calculated, provided the dimensions of the toggle clamp are known.
The toggle clamp system is a machine structure consisting of movable, pin-connected multi-force members that form a stabilized system to transmit forces. The...
Machines: Problem Solving II01:30

Machines: Problem Solving II

Machines are complex structures consisting of movable, pin-connected multi-force members that work together to transmit forces. Consider a lifting tong carrying a 100 kg load. It comprises movable sections DAF and CBG linked together with member AB.

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相关实验视频

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The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
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工业机器人的路径规划基于自适应领域合作采样算法.

Yongbo Zhuang1, Sha Luo1, Qingdang Li1

  • 1College of Electromechanical Engineering, Qingdao University of Science and Technology, Shandong Province, China.

Frontiers in neurorobotics
|December 1, 2025
PubMed
概括

本研究引入了一个自适应现场共同采样 (AFCS) 算法,以增强工业机器人路径规划. AFCS提高了效率和通用性,在复杂的环境中表现优于传统算法.

关键词:
亚洲金融公司 (AFCs)在APF中,APF是APF.在RRT上,RRT是RRT.工业机器人 工业机器人 工业机器人路径规划路径规划路径规划

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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
  • 算法设计 算法设计

背景情况:

  • 工业机器人路径规划面临效率和通用性的挑战.
  • 像快速探索随机树 (RRT) 这样的传统算法在复杂环境中存在局限性.

研究的目的:

  • 为改进工业机器人路径规划提出一个自适应场共采样 (AFCS) 算法.
  • 为了提高路径规划算法的效率,概括能力和稳定性.

主要方法:

  • 开发了一个环境复杂性函数,以利用环境信息.
  • 引入了一个最佳的抽样策略,以提高RRT算法的效率和方向性.
  • 在RRT中集成了一种改进的人工潜力场 (APF) 算法,用于协作节点的确定.

主要成果:

  • 与RRT,RRT*和tRRT相比,AFCS在环境适应性,稳定性和效率方面表现出显著的改善.
  • 在不同复杂性环境中的模拟实验验证了算法的性能.
  • 在ROKAE工业机器人上的实践验证证了算法的适用性.

结论:

  • 拟议的AFCS算法有效地解决了工业机器人的传统路径规划方法的局限性.
  • AFCS为复杂的机器人路径规划任务提供了强大而高效的解决方案.
  • 该算法显示了对现实世界工业应用的巨大潜力.