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Manipulating Deformable Linear Objects: Sensor-Based Skills of Adjustment Motions for Vibration Reduction

机译:操纵可变形线性对象:基于传感器的减震调整运动技巧

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The vibration of a deformable object is often problematic during automatic handling by robot manipulators. However, humans can often handle and damp the vibration of deformable objects with ease. This paper presents force/torque sensor-based skills for handling deformable linear objects in a manner suitable to reduce acute vibration with simple human skill inspired strategies that consist of one or two adjustment motions. The adjustment motion is a simple open-loop motion that can be attached to the end of any arbitrary end-effector's trajectory. As an ordinary industrial robot's simple action, it has three periods, i.e., acceleration, constant speed, and deceleration period; it starts from a predicted time tightly close to a force/moment maximum. The predicted time for the adjustment action is generated automatically on-line based on the vibration rhythm and the data sensed by a force/torque sensor mounted on the robot's wrist. To find the matching point between the vibrational signal of the deformable object and a template, template matching techniques including cross-correlation and minimum squared error methods are used and compared. Experiments are conducted with an industrial robot to test the new skills under various conditions. The results demonstrate that an industrial robot could perform effective vibration reduction skills with simple strategies.
机译:在由机器人操纵器自动操纵期间,可变形物体的振动通常是有问题的。但是,人类通常可以轻松地处理和阻尼可变形物体的振动。本文介绍了基于力/扭矩传感器的技能,该技能可通过一种简单的人类技能启发策略(包括一个或两个调整动作)来处理可变形线性物体,以减少急性振动。调整运动是一个简单的开环运动,可以附加到任意末端执行器轨迹的末端。作为普通工业机器人的简单动作,它具有三个周期,即加速,恒定速度和减速周期。它从紧密接近力/力矩最大值的预测时间开始。根据振动节奏和安装在机器人手腕上的力/扭矩传感器感应到的数据,自动在线生成调整动作的预计时间。为了找到可变形物体的振动信号与模板之间的匹配点,使用并比较了包括互相关和最小平方误差方法的模板匹配技术。用工业机器人进行实验以测试各种条件下的新技能。结果表明,工业机器人可以通过简单的策略执行有效的减振技能。

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