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An adaptive tool-based telerobot control system.

机译:基于自适应工具的远程机器人控制系统。

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摘要

Modern telerobotics concepts seek to improve the work efficiency and quality of remote operations. The unstructured nature of typical remote operational environments makes autonomous operation of telerobotic systems difficult to achieve. Thus, human operators must always remain in the control loop for safety reasons. Remote operations involve tooling interactions with task environment. These interactions can be strong enough to promote unstable operation sometimes leading to system failures. Interestingly, manipulator/tooling dynamic interactions have not been studied in detail. This dissertation introduces a human-machine cooperative telerobotic (HMCTR) system architecture that has the ability to incorporate tooling interaction control and other computer assistance functions into the overall control system. A universal tooling interaction force prediction model has been created and implemented using grey system theory. Finally, a grey prediction force/position parallel fuzzy controller has been developed that compensates for the tooling interaction forces. Detailed experiments using a full-scale telerobotics testbed indicate: (i) the feasibility of the developed methodologies, and (ii) dramatic improvements in the stability of manipulator---based on band saw cutting operations. These results are foundational toward the further enhancement and development of telerobot.
机译:现代远程机器人概念试图提高远程操作的工作效率和质量。典型远程操作环境的非结构化性质使得远程机器人系统的自主操作难以实现。因此,出于安全原因,操作人员必须始终留在控制回路中。远程操作涉及工具与任务环境的交互。这些相互作用可能足够强大,以促进不稳定的运行,有时会导致系统故障。有趣的是,尚未对机械手/工具动态交互进行详细研究。本文介绍了一种人机协同远程机器人(HMCTR)系统架构,该架构具有将工具交互控制和其他计算机辅助功能集成到整个控制系统中的能力。使用灰色系统理论创建并实现了通用工具相互作用力预测模型。最后,开发了一种灰色预测力/位置并行模糊控制器,用于补偿工具的相互作用力。使用全尺寸遥控机器人试验台进行的详细实验表明:(i)所开发方法的可行性,以及(ii)基于带锯切割操作的机械手稳定性的显着改善。这些结果是进一步增强和发展远程机器人的基础。

著录项

  • 作者

    Zhang, Ge.;

  • 作者单位

    The University of Tennessee.;

  • 授予单位 The University of Tennessee.;
  • 学科 Engineering Mechanical.; Artificial Intelligence.
  • 学位 Ph.D.
  • 年度 2004
  • 页码 177 p.
  • 总页数 177
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 机械、仪表工业;人工智能理论;
  • 关键词

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