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Goal directed design of serial robotic manipulators based on task descriptions.

机译:基于任务描述的串行机器人操纵器的目标导向设计。

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摘要

The goal of robotics is to automate and delegate real-world tasks to robotic manipulators. Today robots are being applied to wide range of tasks; from the very traditional material handling tasks to the very sophisticated tele-robotic surgery. Even though general-purpose manipulators are commonplace they do not guarantee optimal task performance. Task optimized manipulators are more effective and efficient than general purpose manipulators. There is a great need for task optimized industrial manipulators that can perform a certain set of jobs with the best efficiency, in the shortest time, and with the least operating cost and power requirements.;Computing the optimal geometric structure of manipulators is one of the most intricate problems in contemporary robot kinematics. Robotic manipulators are designed and built to perform certain predetermined tasks. It is therefore important to incorporate such task requirements during the design and synthesis of the robotic manipulators. Such task requirements and performance constraints can be specified in terms of the required end-effector positions, orientations and velocities along the task trajectory.;There is a close relation between the structure of the manipulator and its kinematic performance. Robotic researchers have over the years tried to develop a framework to reverse engineer optimal manipulator geometries based on task requirements. Every robotic manipulator can only perform certain set of a set of tasks, and some more efficiently than others. Deciding the best manipulator structure for a required job at the design stage is done mainly on the basis of experience and intuition. The rigorous analysis of a few widely used manipulator structures and a collection of a few ad hoc analytical tools can be of some help. However, the need for a comprehensive framework to reverse engineer manipulator structures from task descriptions that can guarantee optimal task performance under a set of operating constraints is still lacking. The ultimate goal of this task-based design approach is to be able to generate both the kinematic and dynamic parameters from task descriptions and operating constraints.;In this work, we define, develop and test a methodology that can generate optimal manipulator geometric structures based on the task requirements. Another objective of this work is to guarantee task performance under user defined joint constraints. Using this methodology, task-based optimal manipulator structures can be generated that guarantee task performance under set operating constraints.
机译:机器人技术的目标是将现实世界的任务自动化并委派给机器人操纵器。如今,机器人已被应用于各种各样的任务。从非常传统的物料搬运任务到非常复杂的远程机器人手术。即使通用机械手很常见,也不能保证最佳的任务性能。任务优化的操纵器比通用操纵器更有效。迫切需要一种任务优化型工业机械手,该机械手能够以最快的效率,最短的时间,最低的运行成本和功率要求执行一组特定的工作;计算机械手的最佳几何结构是其中之一。现代机器人运动学中最复杂的问题。机械手的设计和制造可以执行某些预定任务。因此,重要的是在机器人操纵器的设计和合成过程中纳入此类任务要求。这样的任务要求和性能约束可以根据沿着任务轨迹的最终执行器位置,方向和速度来指定。机械手的结构与其运动性能之间有着密切的关系。多年来,机器人研究人员一直在尝试开发一种框架,以根据任务要求对最佳机械手的几何形状进行逆向工程。每个机器人操纵器只能执行一组任务中的某些任务,并且某些任务效率更高。在设计阶段决定所需工作的最佳机械手结构主要是基于经验和直觉。对一些广泛使用的操纵器结构进行严格的分析,并收集一些特殊的分析工具可能会有所帮助。但是,仍然缺乏一个全面的框架来从任务描述中逆转工程机械手的结构,以保证在一组操作约束下的最佳任务性能。这种基于任务的设计方法的最终目标是能够从任务描述和操作约束中生成运动学参数和动态参数。在这项工作中,我们定义,开发和测试了一种可以生成最佳操纵器几何结构的方法。对任务的要求。这项工作的另一个目标是在用户定义的联合约束下保证任务性能。使用这种方法,可以生成基于任务的最佳操纵器结构,以保证在设置的操作约束下的任务性能。

著录项

  • 作者

    Patel, Sarosh Hosi.;

  • 作者单位

    University of Bridgeport.;

  • 授予单位 University of Bridgeport.;
  • 学科 Robotics.;Computer science.;Computer engineering.
  • 学位 Ph.D.
  • 年度 2014
  • 页码 157 p.
  • 总页数 157
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 农业化学;
  • 关键词

  • 入库时间 2022-08-17 11:54:07

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