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

被引:0
|
作者
Teke, Burak [1 ]
Lanz, Minna [1 ]
Kamarainen, Joni-Kristian [2 ]
Hietanen, Antti [2 ]
机构
[1] Tampere Univ Technol, Dept Prod Engn, Tampere, Finland
[2] Tampere Univ Technol, Dept Signal Proc, Tampere, Finland
关键词
Human-robot interaction; human-robot collaboration; collaborative robots; trajectory planning; Microsoft Kinect v2; ROS;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页数:6
相关论文
共 50 条
  • [31] The feasibility of using Microsoft Kinect v2 sensors during radiotherapy delivery
    Edmunds, David M.
    Bashforth, Sophie E.
    Tahavori, Fatemeh
    Wells, Kevin
    Donovan, Ellen M.
    JOURNAL OF APPLIED CLINICAL MEDICAL PHYSICS, 2016, 17 (06): : 446 - 453
  • [32] Respiratory gating of an Elekta linac using a Microsoft Kinect v2 system
    Edmunds, D.
    Tang, K.
    Symonds-Tayler, R.
    Donovan, E.
    RADIOTHERAPY AND ONCOLOGY, 2017, 123 : S879 - S880
  • [33] Real-time robot motion control with circulatory fields
    Singh, L
    Stephanou, H
    Wen, J
    1996 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION, PROCEEDINGS, VOLS 1-4, 1996, : 2737 - 2742
  • [34] Programming Real-Time Motion Control Robot Prototype
    Medina-Santiago, A.
    Camas Anzueto, J. L.
    Perez-Patricio, M.
    Valdez-Aleman, E.
    JOURNAL OF APPLIED RESEARCH AND TECHNOLOGY, 2013, 11 : 927 - 931
  • [35] Kinect v2 for Mobile Robot Navigation: Evaluation and Modeling
    Fankhauser, Peter
    Bloesch, Michael
    Rodriguez, Diego
    Kaestner, Ralf
    Hutter, Marco
    Siegwart, Roland
    PROCEEDINGS OF THE 17TH INTERNATIONAL CONFERENCE ON ADVANCED ROBOTICS (ICAR), 2015, : 388 - 394
  • [36] Real-time Rotation invariant Action Recognition using Microsoft Kinect
    Raniapsara, Sarath Sasidaran
    Sahin, Ferat
    2016 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC), 2016, : 4287 - 4292
  • [37] Integrating the Microsoft Kinect With Simulink: Real-Time Object Tracking Example
    Fabian, Joshua
    Young, Tyler
    Jones, James C. Peyton
    Clayton, Garrett M.
    IEEE-ASME TRANSACTIONS ON MECHATRONICS, 2014, 19 (01) : 249 - 257
  • [38] Markerless Motion Management Utilizing Kinect V2 Sensor
    Silverstein, E.
    Snyder, M.
    MEDICAL PHYSICS, 2017, 44 (06) : 3213 - 3213
  • [39] Fast and Robust Mapping with Low-cost Kinect V2 for Photovoltaic Panel Cleaning Robot
    Li, Mantian
    Zhang, Mingming
    Fu, Yu
    Guo, Wei
    Zhong, Xingneng
    Wang, Xin
    Chen, Fei
    IEEE ICARM 2016 - 2016 INTERNATIONAL CONFERENCE ON ADVANCED ROBOTICS AND MECHATRONICS (ICARM), 2016, : 95 - 100
  • [40] Design and Validation of Rule-Based Expert System by Using Kinect V2 for Real-Time Athlete Support
    Orucu, Serkan
    Selek, Murat
    APPLIED SCIENCES-BASEL, 2020, 10 (02):