首页> 外文会议>2018 15th International Conference on Ubiquitous Robots >On Humanoid Co-Robot Locomotion when Mechanically Coupled to a Hman Partner
【24h】

On Humanoid Co-Robot Locomotion when Mechanically Coupled to a Hman Partner

机译:机械耦合到人类伙伴时的类人机器人协同运动

获取原文
获取原文并翻译 | 示例

摘要

This work focuses on the implementation of mechanically coupled tasks between a humanoid robot and a human. The latter focus comes from the push for robots to work with humans in everyday life as an overarching goal for the field. Co-robots, or robots that work alongside humans, may be guided by the humans through physical contact, such as the human grasping the robot's hand to gently guide it along a desired path. In this work the single-handed mechanically coupled task of guiding a robot through a course is implemented with four different methods of human input. These methods include: 1) using only force-torque sensors in the wrist of the robot for the control input from the human while the arm is under high-gain position control, creating a rigid coupling between the human and the robot, 2) using the force-torque sensors in the wrist of the robot for the control input while the arm is under low-gain position control with gravity compensation, creating compliant coupling between the human and the robot, 3) using the position of the end-effector of the robot for the control input while the arm is under low-gain position control with gravity compensation, and 4) using the force-torque sensors in the wrist and the position of the end-effector of the robot for the control input while the arm is under low-gain position control with gravity compensation. Tests are performed on the real-world and simulated adult-size humanoid robot DRC-Hubo++. During these tests the human and robot are walking together “hand in hand” with the human guiding the robot in a “figure eight” path. These tests show that having a compliant arm on the robot, when the human is guiding it via moving its end-effector, is beneficial over a rigid arm.
机译:这项工作的重点是实现人形机器人与人之间机械耦合的任务。后者的重点来自于推动机器人在日常生活中与人类合作,这是该领域的首要目标。协同机器人或与人类并肩工作的机器人可能会被人类通过物理接触进行引导,例如人类抓住机器人的手以沿所需的路径轻轻地引导机器人。在这项工作中,通过四种不同的人工输入方法来实现引导机器人完成课程的单手机械耦合任务。这些方法包括:1)在手臂处于高增益位置控制时,仅使用机器人手腕中的力-扭矩传感器作为来自人的控制输入,从而在人与机器人之间建立刚性耦合; 2)使用机器人手腕上的力-扭矩传感器进行控制输入,而手臂则通过重力补偿进行低增益位置控制,从而在人与机器人之间建立顺应性的耦合; 3)使用机器人末端执行器的位置手臂处于具有重力补偿的低增益位置控制下时用于控制输入的机器人,以及4)使用手臂上手腕中的力-扭矩传感器和机器人的末端执行器的位置进行输入时的控制输入在具有重力补偿的低增益位置控制下。测试是在真实世界和模拟的成人尺寸人形机器人DRC-Hubo ++上进行的。在这些测试中,人类和机器人将“手拉手”走在一起,而人类则以“八字形”的路径引导机器人。这些测试表明,当人类通过移动其末端执行器引导机器人时,在机器人上安装顺应性手臂比使用刚性手臂更具优势。

著录项

  • 来源
  • 会议地点 Honolulu(US)
  • 作者单位

    The Mechanical Engineering Department’, University of Las Vegas, Las Vegas, NV, USA;

    Computer Scientist, The Intelligent Systems Section, Artificial Intelligence, The Naval Research Laboratory (NRL), The Navy Center for Applied Research, Washington, DC, USA;

    The Mechanical Engineering Department, University of Las Vegas, Las Vegas, NV, USA;

    The Mechanical Engineering Department, University of Las Vegas, Las Vegas, NV, USA;

    Roboticist at the Laboratory for Autonomous Systems Research, The Naval Research Laboratory (NRL), The Distributed Autonomous Systems Group, Washington, DC, USA;

    Faculty Appointment, Artificial Intelligence (NCARAI), The U.S. Naval Research Laboratory (NRL), The Navy Center for Applied Research, Washington, DC, USA;

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

    Legged locomotion; Robot sensing systems; Force; Task analysis; Torque;

    机译:腿部运动;机器人传感系统;力;任务分析;扭矩;;
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号