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相关概念视频

Distributed Loads: Problem Solving01:21

Distributed Loads: Problem Solving

Beams are structural elements commonly employed in engineering applications requiring different load-carrying capacities. The first step in analyzing a beam under a distributed load is to simplify the problem by dividing the load into smaller regions, which allows one to consider each region separately and calculate the magnitude of the equivalent resultant load acting on each portion of the beam. The magnitude of the equivalent resultant load for each region can be determined by calculating...

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相关实验视频

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Dynamic Lung Tumor Tracking for Stereotactic Ablative Body Radiation Therapy
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分布式动态任务分配用于移动目标 网络移动机器人的跟踪使用k-WTA网络.

Kexin Liu, Yinyan Zhang

    IEEE transactions on neural networks and learning systems
    |March 25, 2024
    PubMed
    概括

    本研究介绍了一种新的分布式方法,用于合作机器人分配目标跟踪任务. 它使用k-winners-take-all网络进行高效的,无需中央控制的有限时间错误融合.

    科学领域:

    • 机器人技术 机器人技术 机器人技术
    • 控制系统 控制系统
    • 人工智能的人工智能

    背景情况:

    • 任务分配对于合作机器人至关重要.
    • 现有的方法通常需要中央控制或共识过器.

    研究的目的:

    • 为目标追踪中的移动机器人提出一种全新的,完全分布式的任务分配方法.
    • 在不依赖共识过器或中央单元的情况下实现有限时间错误的融合.

    主要方法:

    • 一个分布式k-winners-take-all (k-WTA) 网络被用来选择最接近目标的k个机器人.
    • 设计了一种具有速度反和非线性激活功能的创新机器人控制规律.
    • 国家信息仅在通信邻国之间共享.

    主要成果:

    • 提出的方法实现了有限时间误差的趋同.
    • 它消除了对k-WTA结果的中央计算单元的需求.
    • 与传统方法相比,模拟显示的总移动距离和速度规范较小.

    结论:

    • 新的分布式任务分配方法在动态环境中提高了效率和性能.

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  • 这种方法为合作型移动机器人系统提供了分散和有效的解决方案.