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Kinematic Modeling of a RHex-type Robot Using a Neural Network

机译:使用神经网络的RHex型机器人的运动学建模

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摘要

Motion planning for legged machines such as RHex-type robots is far less developed than motion planning for wheeled vehicles. One of the main reasons for this is the lack of kinematic and dynamic models for such platforms. Physics based models are difficult to develop for legged robots due to the difficulty of modeling the robot-terrain interaction and their overall complexity. This paper presents a data driven approach in developing a kinematic model for the X-RHex Lite (XRL) platform. The methodology utilizes a feed-forward neural network to relate gait parameters to vehicle velocities.
机译:腿部机械(例如RHex型机器人)的运动计划远没有轮式车辆的运动计划发展。造成这种情况的主要原因之一是此类平台缺乏运动学和动态模型。由于难以对机器人与地面的相互作用进行建模及其整体复杂性,因此难以为有腿机器人开发基于物理的模型。本文为开发X-RHex Lite(XRL)平台的运动学模型提供了一种数据驱动的方法。该方法利用前馈神经网络将步态参数与车辆速度相关联。

著录项

  • 来源
    《Unmanned Systems Technology XIX》|2017年|1019507.1-1019507.9|共9页
  • 会议地点 Anaheim(US)
  • 作者单位

    Department of Scientific Computing, Florida State University, Tallahassee, FL, USA;

    Department of Mechanical Engineering, Florida AM - Florida State University, College of Engineering, Tallahassee, FL, USA;

    Department of Mechanical Engineering, Florida AM - Florida State University, College of Engineering, Tallahassee, FL, USA;

    Department of Mechanical Engineering, Florida AM - Florida State University, College of Engineering, Tallahassee, FL, USA;

    Department of Mechanical Engineering, Florida AM - Florida State University, College of Engineering, Tallahassee, FL, USA;

  • 会议组织
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Legged Robots; Kinematic Modeling; Neural Network;

    机译:腿式机器人运动学建模;神经网络;

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