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GraspIt!: A versatile simulator for robotic grasping.

机译:GraspIt !:用于机器人抓取的多功能模拟器。

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摘要

Grasping in an industrial setting is generally accomplished with low complexity grippers which offer a high degree of reliability within a structured environment. But, as robots are moved out of the factory into more unstructured settings, they will need more flexible devices to grasp or manipulate objects. To fill this need, articulated hands are being designed with more and more degrees of freedom, but this additional flexibility comes at a price of additional complexity in the design process and in choosing a grasp from the large number of possibilities. Mechanical grasping theory, which has been thoroughly studied in the last 20 years, provides objective methods for evaluating grasps, but the field has lacked a tool that can apply this analysis to arbitrary grasps of objects using different robotic hands.; This thesis presents a grasping simulator that can aid both robotic hand designers and those planning grasping tasks. It provides a user with an interactive environment where he or she can manipulate the degrees of freedom of any given hand model to form grasps. As contact between the links of the hand and an object occur, the simulator analyzes the new grasp on the fly and provides the user with instant feedback concerning the quality of the grasp. This information includes not only numerical quality measures, but also an indication of the grasp's weak point as well as projections of the 6-dimensional space of forces and torques that can be applied by the grasp.; In addition to its visualization capabilities, the simulator has facilities for modeling a complete robotic work cell, which is necessary when planning an actual grasping task. When combined with a real-time, model-based vision system to align the pose of a simulated object with the pose of an actual object in the workspace, the simulator can be used to plan, execute, and monitor a complete grasping task. Examples of this process are presented and serve to demonstrate this application of the simulator.; Finally, the addition of a module to simulate object dynamics further increases the realism of the simulation. With it, a user can examine the grasp formation process to ensure that a desired grasp can be achieved. Examples in this section demonstrate the benefit of going beyond a spatial analysis and including the temporal dimension.
机译:工业环境中的抓取通常是通过低复杂度的抓取器完成的,该抓取器在结构化环境中提供高度的可靠性。但是,随着机器人从工厂搬迁到更加非结构化的环境中,他们将需要更灵活的设备来抓取或操纵物体。为了满足这种需求,关节式手的设计越来越自由,但是这种额外的灵活性是以设计过程中的复杂性以及从众多可能性中选择抓握为代价的。在过去的20年中,对机械抓紧理论进行了深入研究,它为评估抓握力提供了客观的方法,但是该领域缺乏一种工具,可以将这种分析应用于使用不同机械手的任意抓握物体。本文提出了一种抓握模拟器,可以帮助机械手设计师和那些计划抓握任务的人使用。它为用户提供了一个交互式环境,在该环境中,他或她可以操纵任何给定手部模型的自由度以形成抓握。当手和物体的链接之间发生接触时,模拟器会动态分析新的抓握,并为用户提供有关抓握质量的即时反馈。该信息不仅包括数值质量度量,还包括抓地力薄弱点的指示以及抓地力可以施加的力和扭矩的6维空间的投影。除了其可视化功能外,模拟器还具有对完整的机器人工作单元进行建模的功能,这在计划实际的抓取任务时必不可少。当与基于模型的实时视觉系统结合以使模拟对象的姿势与工作空间中实际对象的姿势对齐时,模拟器可以用于计划,执行和监视完整的抓取任务。给出了该过程的示例,并用于演示模拟器的这种应用。最后,增加了模拟对象动力学的模块,进一步提高了模拟的真实性。使用它,用户可以检查抓握形成过程以确保可以实现期望的抓握。本节中的示例演示了超越空间分析并包括时间维度的好处。

著录项

  • 作者

    Miller, Andrew Tesch.;

  • 作者单位

    Columbia University.;

  • 授予单位 Columbia University.;
  • 学科 Computer Science.
  • 学位 Ph.D.
  • 年度 2001
  • 页码 127 p.
  • 总页数 127
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 自动化技术、计算机技术;
  • 关键词

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