Real-time and Robust Collaborative Robot Motion Control with Microsoft Kinect ® v2

Burak Teke, Minna Lanz, J. Kämäräinen, A. Hietanen
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引用次数: 9

Abstract

Recent development in depth sensing provide various opportunities for the development of new methods for Human Robot Interaction (HRI). Collaborative robots (co-bots) are redefining HRI across the manufacturing industry. However, little work has been done yet in the field of HRI with Kinect sensor in this industry. In this paper, we will present a HRI study using nearest-point approach with Microsoft Kinect v2 sensor’s depth image (RGB-D). The approach is based on the Euclidean distance which has robust properties against different environments. The study aims to improve the motion performance of Universal Robot–5 (UR5) and interaction efficiency during the possible collaboration using the Robot Operating System (ROS) framework and its tools. After the depth data from the Kinect sensor has been processed, the nearest points differences are transmitted to the robot via ROS.
实时和鲁棒协作机器人运动控制与微软Kinect®v2
深度传感的最新发展为开发人机交互(HRI)新方法提供了各种机会。协作机器人(co-bots)正在整个制造业重新定义人力资源管理(HRI)。然而,在这个行业中,Kinect传感器在HRI领域的工作还很少。在本文中,我们将使用最近点方法与微软Kinect v2传感器的深度图像(RGB-D)进行HRI研究。该方法基于欧几里得距离,对不同环境具有鲁棒性。本研究旨在利用机器人操作系统(ROS)框架及其工具,提高Universal Robot - 5 (UR5)在可能的协作过程中的运动性能和交互效率。Kinect传感器的深度数据经过处理后,最近的点差通过ROS传输给机器人。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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