基于虚拟关节力矩传感的协作机器人碰撞检测与接触点估计

Dario Zurlo, T. Heitmann, M. Morlock, Alessandro De Luca
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摘要

在人机物理交互(pHRI)中,可靠地估计和定位机器人与环境之间的接触力是至关重要的。本文提出了一种完整的接触检测、隔离和反应方案,并在一种新型六自由度工业协作机器人上进行了测试。我们结合了两种流行的方法,基于监测能量和广义动量,以更稳健的方式检测和隔离整个机器人身体上的碰撞。实验结果表明了我们在LARA 5协作机器人上实现的有效性,该机器人仅依赖于电机电流和关节编码器的测量。为了验证目的,还使用外部GTE CoboSafe传感器测量接触力。在碰撞检测成功后,结合基于广义动量的残差法和接触粒子滤波(CPF)方案分离接触点位置。我们首次展示了在真实机器人上成功实现这种组合,而不依赖于关节扭矩传感器测量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Collision Detection and Contact Point Estimation Using Virtual Joint Torque Sensing Applied to a Cobot
In physical human-robot interaction (pHRI) it is essential to reliably estimate and localize contact forces between the robot and the environment. In this paper, a complete contact detection, isolation, and reaction scheme is presented and tested on a new 6-dof industrial collaborative robot. We combine two popular methods, based on monitoring energy and generalized momentum, to detect and isolate collisions on the whole robot body in a more robust way. The experimental results show the effectiveness of our implementation on the LARA 5 cobot, that only relies on motor current and joint encoder measurements. For validation purposes, contact forces are also measured using an external GTE CoboSafe sensor. After a successful collision detection, the contact point location is isolated using a combination of the residual method based on the generalized momentum with a contact particle filter (CPF) scheme. We show for the first time a successful implementation of such combination on a real robot, without relying on joint torque sensor measurements.
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