The purpose of this paper is to generate grinding trajectory of unknown model parts simply and efficiently. In this paper, a method of grinding trajectory generation of hybrid robot based on Cartesian space direct teaching technology is proposed.
This method first realizes the direct teaching of hybrid robot based on 3Dconnexion SpaceMouse (3DMouse) sensor, and the full path points of the robot are recorded in the teaching process. To reduce the jitter and make the speed control more freely when dragging the robot, the sensor data is processed by Kalman filter, and a variable admittance control model is established. And the joint constraint processing is given during teaching. After that, the path points are modified and fitted into double B-splines, and the speed planning is performed to generate the final grinding trajectory.
Experiment verifies the feasibility of using direct teaching technology in Cartesian space to generate grinding trajectory of unknown model parts. By fitting all the teaching points into cubic B-spline, the smoothness of the grinding trajectory is improved.
The whole method is verified by the self-developed TriMule-600 hybrid robot, and it can also be applied to other industrial robots.
The main contribution of this paper is to realize the direct teaching and trajectory generation of the hybrid robot in Cartesian space, which provides an effective new method for the robot to generate grinding trajectory of unknown model parts.
This work is partially supported by National Key R&D program of China (Grant No. 2017YFB1301800), National Natural Science Foundation of China (grants 91948301 and 51721003) and EU H2020-RISE-ECSASDP (grant 734272).
Conflict of interest: The author(s) declared no potential conflicts of interest with respect to the research, authorship and/or publication of this paper.
Xiao, J., Wang, Y., Liu, S., Sun, Y., Liu, H., Huang, T. and Xu, J. (2021), "Grinding trajectory generation of hybrid robot based on Cartesian direct teaching technology", Industrial Robot, Vol. 48 No. 3, pp. 341-351. https://doi.org/10.1108/IR-09-2020-0194
Emerald Publishing Limited
Copyright © 2020, Emerald Publishing Limited