Robot programming by demonstration: a novel system for robot trajectory programming based on robot operating system

In this article, a new trajectory programming system that allows non-expert users to intuitively and efficiently program trajectories for robots is proposed. The system tracks a pen-shaped marker and obtains its position and orientation by processing the point cloud data of the workspace. A graphical user interface, which enables users to save and execute the acquired trajectory immediately after performing trajectory demonstration, is designed and developed for the system. The performance of the developed system is experimentally evaluated by using it to program trajectories for a UR5 robot. The results indicate that compared with traditional kinesthetic programming, the developed system has the potential of significantly reducing the ergonomic stress and workload of users. The system is developed based on the robot operating system, which facilitates its integration with different robot control systems.

[1]  Jan Noyes.  Review of Handbook of human-computer interaction edited by Helander, MG, Landauer, TK & Prabhu, PV , 1999 .

[2]  Guilin Yang,et al.  Intuitive robot tool path teaching using laser and camera in Augmented Reality environment , 2010, 2010 11th International Conference on Control Automation Robotics & Vision.

[3]  P. Rousseeuw.  Least Median of Squares Regression , 1984 .

[4]  Stefan Schaal,et al.  http://www.jstor.org/about/terms.html. JSTOR's Terms and Conditions of Use provides, in part, that unless you have obtained , 2007 .

[5]  Kourosh Khoshelham,et al.  Accuracy analysis of kinect depth data , 2012 .

[6]  Jing Li Wang,et al.  Color image segmentation: advances and prospects , 2001, Pattern Recognit..

[7]  John Norrish,et al.  Recent Progress on Programming Methods for Industrial Robots , 2010, ISR/ROBOTIK.

[8]  X. Zhang,et al.  Teaching-playback of robot manipulator based on human gesture recognition and motion tracking , 2015, 2015 IEEE International Conference on Robotics and Biomimetics (ROBIO).

[9]  John Pretlove,et al.  Augmented reality for programming industrial robots , 2003, The Second IEEE and ACM International Symposium on Mixed and Augmented Reality, 2003. Proceedings..

[10]  T. Landauer,et al.  Handbook of Human-Computer Interaction , 1997 .

[11]  Fabio Remondino,et al.  A REVIEW OFPOINT CLOUDS SEGMENTATION AND CLASSIFICATION ALGORITHMS , 2017 .

[12]  Anh Nguyen,et al.  3D point cloud segmentation: A survey , 2013, 2013 6th IEEE Conference on Robotics, Automation and Mechatronics (RAM).

[13]  Jörg Krüger,et al.  Markerless gesture-based motion control and programming of industrial robots , 2011, ETFA2011.

[14]  Andrew Y. C. Nee,et al.  Augmented reality applications in manufacturing: a survey , 2008 .

[15]  Robert C. Bolles,et al.  A RANSAC-Based Approach to Model Fitting and Its Application to Finding Cylinders in Range Data , 1981, IJCAI.

[16]  Geoffrey Biggs,et al.  A Survey of Robot Programming Systems , 2010 .

[17]  Jörg Krüger,et al.  Spatial programming for industrial robots based on gestures and Augmented Reality , 2012, 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[18]  Signe Moe,et al.  Real-time hand guiding of industrial manipulator in 5 DOF using Microsoft Kinect and accelerometer , 2013, 2013 IEEE RO-MAN.

[19]  Stefan Schaal,et al.  Robot Programming by Demonstration , 2009, Springer Handbook of Robotics.

[20]  Aude Billard,et al.  Learning from Humans , 2016, Springer Handbook of Robotics, 2nd Ed..

[21]  Azriel Rosenfeld,et al.  Robust regression methods for computer vision: A review , 1991, International Journal of Computer Vision.

[22]  Jörg Krüger,et al.  Robust finger gesture recognition on handheld devices for spatial programming of industrial robots , 2013, 2013 IEEE RO-MAN.