Journal of Intelligent & Robotic Systems

, Volume 97, Issue 1, pp 67–79 | Cite as

A Vision-Based Coordinated Motion Scheme for Dual-Arm Robots

  • Xianlun Wang
  • Longfei ChenEmail author


With the rise of service robots, research on cooperation between two-arm robots has become increasingly important. In this paper, two NAO two-armed robots are used as the experimental platform and are combined with projective geometry, vision, robotics and other knowledge to carry out theoretical derivation and experiments on the coordinated movements of dual-arm robots. From the aspect of visual information processing, we analyse and solve the detailed target recognition process. Then, on this basis, we propose a set of complete coordinated motion control schemes. For object recognition, in this paper, we propose a highly adaptable linear stick recognition method. To solve the control flow of coordinated movement, we calculate the inverse kinematics of the unreachable pose of a single NAO manipulator by ignoring the degree of freedom of rotation around an end axis, and propose a trajectory planning method for the vertical constraint relationship between the tool and the workpiece plane in the coordinated manipulator movement. A comparison of the results of a simulation and a real experiment reveals that the trajectories of a workpiece clamped at the ends of the two robots’ mechanical arms are roughly the same; consequently, the coordinated control scheme proposed in this paper is feasible. Moreover, the scheme proposed in this paper is sufficiently accurate to meet service robot applications in daily life. Because the joint active clearance of the NAO robot arm is large and its sensor sensitivity is high, clearance change can be used in the future to replace the force sensor for hybrid control.


Dual-arm robots Coordinated motion NAO robot Visual positioning 


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This work was supported by the National Natural Science Foundation of China (No.51105213), The Key Research and Development Program of Shandong Province (2017GGX10133, 2018GNC112007), Basic Research Project of Science and Technology Program of Qingdao City (No. 13-1-4-208-jch) and Natural Science Foundation of Shandong Province (No.ZR2015EM035).


  1. 1.
    Siciliano, B., Khatib, O.: Springer Handbook of Robotics. Springer (2016)Google Scholar
  2. 2.
    Siradjuddin, I., Behera, L., McGinnity, T.M., Coleman, S.: A position based visual tracking system for a 7 DOF robot manipulator using a kinect camera. In: The 2012 International Joint Conference on Neural Networks (IJCNN), pp. 1–7 (2012)Google Scholar
  3. 3.
    Liegeois, A.: Automatic supervisory control of the configuration and behaviour of multibody mechanisms. IEEE Trans. Syst. Man Cybern. 7(12), 868–871 (1977)CrossRefGoogle Scholar
  4. 4.
    Wang, J.G., Li, Y., Zhao, X.: Inverse kinematics and control of a 7-DOF redundant manipulator. Int. J. Adv. Rob. Syst. 7(4), 1–9 (2010)Google Scholar
  5. 5.
    Kim, J., Sin, M., Lee, J., Kim, D.-H., Lim, H.-K., Kim, S.-R.: Kinematics analysis and motion planning for a 7-DOF redundant industrial robot manipulator. In: 2011 11th International conference on control, automation and systems, pp. 522–527. IEEE (2011)Google Scholar
  6. 6.
    Crenganis, M., Breaz, R., Racz, G., Bologa, O.: Inverse kinematics of a 7 DOF manipulator using adaptive neuro-fuzzy inference systems. In: 2012 12th International Conference on Control Automation Robotics & Vision (ICARCV), pp. 1232–1237. IEEE (2012)Google Scholar
  7. 7.
    Mason, M.T.: Compliance and force control for computer controlled manipulators. IEEE Trans. Syst. Man. Cybern. 11(6), 418–432 (1981)CrossRefGoogle Scholar
  8. 8.
    Zheng, Y.F., Luh, J.Y.S.: Control of two coordinated robots in motion. In: 1985 24th IEEE Conference on Decision and Control, pp. 1761–1766. IEEE (1985)Google Scholar
  9. 9.
    Nakano, E.: Cooperational control of the anthropomorphous manipulator” melarm”. In: Proc. of 4th International Symposium on Industrial Robots, pp. 251–260 (1974)Google Scholar
  10. 10.
    Uchiyama, M., Dauchez, P.: A symmetric hybrid position/force control scheme for the coordination of two robots. In: 1988 IEEE International Conference on Robotics and Automation, 1988. Proceedings, pp. 350–356. IEEE (1988)Google Scholar
  11. 11.
    Kruse, D., Wen, J.T., Radke, R.J.: A sensor-based dual-arm tele-robotic system. IEEE Trans. Autom. Sci. Eng. 12(1), 4–18 (2015)CrossRefGoogle Scholar
  12. 12.
    Caccavale, F., Chiacchio, P., Marino, A., Villani, L.: Six-DOF impedance control of dual-arm cooperative manipulators. IEEE/ASME Trans. Mechatron. 13(5), 576–586 (2008)CrossRefGoogle Scholar
  13. 13.
    Shamsuddin, S., Ismail, L.I., Yussof, H., Zahari, N.I., Bahari, S., Hashim, H., Jaffar, A.: Humanoid robot NAO: Review of control and motion exploration. In: 2011 IEEE International Conference on Control System, Computing and Engineering (ICCSCE), pp. 511–516. IEEE (2011)Google Scholar
  14. 14.
    Shamsuddin, S., Yussof, H., Ismail, L., Hanapiah, F.A., Mohamed, S., Piah, H.A., Zahari, N.I.: Initial response of autistic children in human-robot interaction therapy with humanoid robot NAO. In: 2012 IEEE 8th International Colloquium on Signal Processing and its Applications (CSPA), pp. 188–193. IEEE (2012)Google Scholar
  15. 15.
    Wu, F.C.: Mathematical Methods in Computer Vision. Science Press (2008)Google Scholar
  16. 16.
    Lam, L., Lee, S.-W., Suen, C.Y.: Thinning methodologies-a comprehensive survey. IEEE Trans. Pattern Anal. Mach. Intell. 14(9), 869–885 (1992)CrossRefGoogle Scholar
  17. 17.
    Zhang, T.Y., Suen, C.Y.: A fast parallel algorithm for thinning digital patterns. Commun. ACM 27(3), 236–239 (1984)CrossRefGoogle Scholar
  18. 18.
    He, L., Chao, Y., Suzuki, K.: A run-based two-scan labeling algorithm. IEEE Trans. Image. Process. 17(5), 749–756 (2008)MathSciNetCrossRefGoogle Scholar
  19. 19.
    Kofinas, N., Orfanoudakis, E., Lagoudakis, M.G.: Complete analytical forward and inverse kinematics for the Nao humanoid robot. J. Intell. Robot. Syst. 77(2), 251–264 (2015)CrossRefGoogle Scholar
  20. 20.
    Mayer, G.E., Paul, R.P., Shimano, B.: Differential kinematic control equations for simple manipulators. IEEE Trans. Syst. Man Cybern., 1(1) (1981)Google Scholar

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© Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.College of Electromechanical EngineeringQingdao University of Science and TechnologyQingdaoChina

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