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Collision detection of humanoid robot arm under model uncertainties for handling of unknown object

机译:文体机器人在模型不确定性下处理未知物体的碰撞检测

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In recent years human-robot collision safety has received considerable attention. Thus, various collision detection algorithms have been proposed to ensure human-robot collision safety, and these algorithms are usually model-based. However, the dynamic model of a robot arm is uncertain or unknown in cases where the arm performs a task with various objects or tools. In this paper, we propose a collision detection method for a robot arm that changes its tools or pick up various objects. For this purpose, a novel collision detection index, which is decoupled from the inevitable external force generated by the object being handled by the robot, is developed. The proposed index is verified through various simulations using a 7-DOF robot arm, and the corresponding results show that regardless of the object that is being handled, it is possible to detect collisions.
机译:近年来人机机器人碰撞安全得到了相当大的关注。因此,已经提出了各种碰撞检测算法以确保人机机器人碰撞安全性,并且这些算法通常是基于模型的。然而,在手臂用各种对象或工具执行任务的情况下,机器人臂的动态模型是不确定的或未知的。在本文中,我们提出了一种用于改变其工具或拾取各种对象的机器人臂的碰撞检测方法。为此目的,开发了一种新的碰撞检测指数,其从由机器人处理的物体产生的不可避免的外力分离的碰撞检测指标。通过使用7-DOF机器人臂进行各种模拟验证所提出的索引,并且相应的结果表明,无论是否处理的对象如何,都可以检测冲突。

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