004

industrial robot, robotics 3D scanning, off-line programming.

In the paper the assessment of the feasibility of using a selected off-line robot programming environment in the design process of a robotic 3D scanning process was presented. First of all, basic information about modern industrial robots implementations were outlined. Secondly, a developed virtual model of an analyzed robotic cell was described. Moreover, analyses on selected aspects of the considered issue were discussed. The study has confirmed that utilization of OLP method is very useful and needed for improvement of robotic production processes.

1. Berga J., Reinharta G. An Integrated Planning and Programming System for Human-Robot-Cooperation. Procedia CIRP. 2017. Vol. 63. P. 95–100.
2. Wilson M. Implementation of Robot Systems: An Introduction to Robotics. Automation and Successful Systems Integration in Manufacturing, Butterworth-Heinemann, 2014.
3. Casalino A., Cividini F., Zanchettin A.M., Piroddi L., Piroddi A., Rocco P. Human-robot collaborative assembly: a use-case application. IFAC-PapersOnLine. 2018. Vol. 51. No. 11. P. 194–199.
4. Yin S., Ren Y., Guo Y., Zhu J., Yang S., Ye S. Development and calibration of an integrated 3D scanning system for high-accuracy large-scale metrology. Measurement. 2014. 54. P. 65–76.
5. Sobaszek Ł., Szczypiór D., Gola A. Programowanie off-line jako narzędzie projektowania i testowania zrobotyzowanych stanowisk produkcyjnych. Innowacje w elektronice, informatyce i inżynierii produkcji, T. 2. 2021. Р. 173–187. [In Polish].
6. Tereshchuk V., Stewart J., Bykov N., Pedigo S., Devasia S., Banerjee A. G. An efficient scheduling algorithm for multi-robot task allocation in assembling aircraft structures. IEEE Robot. Autom. Lett. 2019. 4. P. 3844–3851.
7. Ericsson M., Nylén P. A look at the optimization of robot welding speed based on process modeling: Integrating robot simulation, finite element analysis, and numerical optimization provides a powerful tool for constructing and optimizing off-line robot torch trajectories and process parameters. Welding Journal. 2007. 86. P. 238–244.
8. Baizid K., Meddahi A., Yousnadj A., Chellali R., Khan H., Iqbal J. Robotized task time scheduling and optimization based on Genetic Algorithms for non redundant industrial manipulators. Proceedings of the 2014 IEEE International Symposium on Robotic and Sensors Environments (ROSE) Proceedings, Timisoara. Romania. 16–18 October 2014.
9. Mohsin I., He K., Li Z., Du, R. Path Planning under Force Control in Robotic Polishing of the Complex Curved Surfaces. Applied Sciences. 2019. 9. 5489.
10. Zacharia P. Th., Xidias E. K., Aspragathos N. A. Task scheduling and motion planning for an industrial manipulator. Robotics and Computer-Integrated Manufacturing. 2013. 29 (6). Р. 449–462.
11. Das S. D., Bain V., Rakshit P. Energy Optimized Robot Arm Path Planning Using Differential Evolution in Dynamic Environment. Second International Conference on Intelligent Computing and Control Systems (ICICCS). 2018. Р. 1267–1272.
12. Rubio F., Valero F., Suñer J. L., Mata V. A Comparison of Algorithms for Path Planning of Industrial Robots. Proceedings of EUCOMES08, Ceccarelli M., Eds.; Springer, Dordrecht, 2009.
13. Alatartsev S. Robot Trajectory Optimization for Relaxed Effective Tasks. Otto von Guericke University Magdeburg, Magdeburg, Germany, 2015.
14. Kawasaki Heavy Industries. Kawasaki Robot Materials, AS Language Programming, 2020.
15. Kawasaki Heavy Industries. Standard Specifications RS003N-A, 2020.
16. ARTEC 3D. Professional 3D scanners, https://www.artec3d.com, 2022.

1. Berga J., Reinharta G. An Integrated Planning and Programming System for Human-Robot-Cooperation. Procedia CIRP. 2017. Vol. 63. P. 95–100.
2. Wilson M. Implementation of Robot Systems: An Introduction to Robotics. Automation and Successful Systems Integration in Manufacturing, Butterworth-Heinemann, 2014.
3. Casalino A., Cividini F., Zanchettin A.M., Piroddi L., Piroddi A., Rocco P. Human-robot collaborative assembly: a use-case application. IFAC-PapersOnLine. 2018. Vol. 51. No. 11. P. 194–199.
4. Yin S., Ren Y., Guo Y., Zhu J., Yang S., Ye S. Development and calibration of an integrated 3D scanning system for high-accuracy large-scale metrology. Measurement. 2014. 54. P. 65–76.
5. Sobaszek Ł., Szczypiór D., Gola A. Programowanie off-line jako narzędzie projektowania i testowania zrobotyzowanych stanowisk produkcyjnych. Innowacje w elektronice, informatyce i inżynierii produkcji, T. 2. 2021. Р. 173–187. [In Polish].
6. Tereshchuk V., Stewart J., Bykov N., Pedigo S., Devasia S., Banerjee A. G. An efficient scheduling algorithm for multi-robot task allocation in assembling aircraft structures. IEEE Robot. Autom. Lett. 2019. 4. P. 3844–3851.
7. Ericsson M., Nylén P. A look at the optimization of robot welding speed based on process modeling: Integrating robot simulation, finite element analysis, and numerical optimization provides a powerful tool for constructing and optimizing off-line robot torch trajectories and process parameters. Welding Journal. 2007. 86. P. 238–244.
8. Baizid K., Meddahi A., Yousnadj A., Chellali R., Khan H., Iqbal J. Robotized task time scheduling and optimization based on Genetic Algorithms for non redundant industrial manipulators. Proceedings of the 2014 IEEE International Symposium on Robotic and Sensors Environments (ROSE) Proceedings, Timisoara. Romania. 16–18 October 2014.
9. Mohsin I., He K., Li Z., Du, R. Path Planning under Force Control in Robotic Polishing of the Complex Curved Surfaces. Applied Sciences. 2019. 9. 5489.
10. Zacharia P. Th., Xidias E. K., Aspragathos N. A. Task scheduling and motion planning for an industrial manipulator. Robotics and Computer-Integrated Manufacturing. 2013. 29 (6). Р. 449–462.
11. Das S. D., Bain V., Rakshit P. Energy Optimized Robot Arm Path Planning Using Differential Evolution in Dynamic Environment. Second International Conference on Intelligent Computing and Control Systems (ICICCS). 2018. Р. 1267–1272.
12. Rubio F., Valero F., Suñer J. L., Mata V. A Comparison of Algorithms for Path Planning of Industrial Robots. Proceedings of EUCOMES08, Ceccarelli M., Eds.; Springer, Dordrecht, 2009.
13. Alatartsev S. Robot Trajectory Optimization for Relaxed Effective Tasks. Otto von Guericke University Magdeburg, Magdeburg, Germany, 2015.
14. Kawasaki Heavy Industries. Kawasaki Robot Materials, AS Language Programming, 2020.
15. Kawasaki Heavy Industries. Standard Specifications RS003N-A, 2020.
16. ARTEC 3D. Professional 3D scanners, https://www.artec3d.com, 2022.