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Robotic goal-based semi-autonomous algorithms improve remote operator performance.

机译：基于机器人目标的半自治算法提高了远程操作员的性能。

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摘要

The focus of this research was to determine if reliable goal-based semi-autonomous algorithms are able to improve remote operator performance or not. Two semi-autonomous algorithms were examined: visual servoing and visual dead reckoning. Visual servoing uses computer vision techniques to generate movement commands while using internal properties of the camera combined with sensor data that tell the robot its current position based on its previous position. This research shows that the semi-autonomous algorithms developed increased performance in a measurable way. An analysis of tracking algorithms for visual servoing was conducted and tracking algorithms were enhanced to make them as robust as possible. The developed algorithms were implemented on a currently fielded military robot and a human-in-the-loop experiment was conducted to measure performance.
机译：这项研究的重点是确定可靠的基于目标的半自治算法是否能够提高远程操作员的性能。研究了两种半自治算法：视觉伺服和视觉航位推算。视觉伺服使用计算机视觉技术来生成运动命令，同时将相机的内部属性与传感器数据结合使用，这些数据根据机器人的先前位置告诉机器人其当前位置。这项研究表明，半自治算法以可衡量的方式提高了性能。进行了视觉伺服跟踪算法的分析，并对跟踪算法进行了增强，以使其尽可能强大。所开发的算法是在当前部署的军用机器人上实施的，并且进行了在环实验以测量性能。

著录项

  • 作者

    Hunt, Shawn.;

  • 作者单位

    Wayne State University.;

  • 授予单位 Wayne State University.;
  • 学科 Engineering Robotics.
  • 学位 Ph.D.
  • 年度 2010
  • 页码 159 p.
  • 总页数 159
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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