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Orientation planning of robot end-effector using augmented reality

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Abstract

This paper presents a methodology for planning the orientation of the end-effector for an industrial robot based on the application of augmented reality. The targeted applications are those where the end-effector is constrained to follow a visible path, which position and model are unknown, at suitable inclination angles with respect to the path. The proposed approach enables the users to create a list of control points interactively on a parameterized curve model, define the orientation of the end-effector associated with each control point, and generate a ruled surface representing the path to be planned. An approximated time-optimal trajectory, which is a determined subject to robot actuators and joint velocity constraints using convex optimization techniques, is implemented to simulate a virtual robot, allowing the users to visually evaluate the trajectory planning process. A case study is presented and discussed.

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References

  1. World Robotics (2010). Exclusive Summary of World Robotics 2010. Available from http://www.worldrobotics.org/downloads/2010_Executive_Summary_rev.pdf. Accessed 3 February 2012

  2. Pires JN, Veiga G, Araújo R (2009) Programming-by-demonstration in the coworker scenario for SMEs. Ind Robot Int J 36(1):73–83

    Article  Google Scholar 

  3. Thrun S (2004) Toward a framework for human–robot interaction. Hum Comput Interact 19(1/2):9–24

    Article  Google Scholar 

  4. Liu Z, Bu W, Tan J (2010) Motion navigation for arc welding robots based on feature mapping in a simulation environment. Robot Comput Integr Manuf 26(2):137–144

    Article  Google Scholar 

  5. Ong SK, Chong JWS, Nee AYC (2010) A novel AR-based robot programming and path planning methodology. Robot Comput Integr Manuf 26(3):240–249

    Article  Google Scholar 

  6. Zaeh MF, Vogl W (2006). Interactive laser-projection for programming industrial robots. In: Proceedings of the International Symposium on Mixed and Augmented Reality, Santa Barbara, CA, 22–25 October, pp. 125–128

  7. Reinhart G, Munzert U, Vogl W (2008) A programming system for robot-based remote-laser-welding with conventional optics. CIRP Ann Manuf Technol 57(1):37–40

    Article  Google Scholar 

  8. AVILUS (2011). http://www.avilus.de/. Accessed 3 February 2012

  9. SMErobot (2009). The European robot initiative for strengthening the competitiveness of SMEs in manufacturing: the robot capable of understanding human-like instructions. Available from http://www.smerobot.org/15_final_workshop/download/presentations/02_New_devices_and_methods_20090507.pdf. Accessed 3 February 2012

  10. Hollmann R, Hägele M, Verl A (2010). Learning probabilistic models to enhance the efficiency of programming-by-demonstration for industrial robots. In: Proceedings of the International Symposium on Robotics. Munich, Germany, 7–9 June

  11. ARVIKA Konsortium (2001). Available from http://www.arvika.de/www/pdf/flyer_e.pdf. Accessed 3 February 2012

  12. Chintamani K, Cao A, Ellis RD, Pandya AK (2010) Improved tele-manipulator navigation during display-control misalignments using augmented reality cues. IEEE Trans Syst Man Cybern Syst Hum 40(1):29–39

    Article  Google Scholar 

  13. Kheddar A, Chellali R, Coiffet P (2000) Virtual environment assisted tele-operation. In: Stanney KM (ed) The handbook of virtual environment technology. Erlbaum, Mahwah, pp 959–997

    Google Scholar 

  14. Vericut (2012). Robot simulation. Available from http://cgtech.com/usa/cnc-robots/. Accessed 3 February 2012

  15. Siemens (2012). Tecnomatix robotics and automation planning. Available from http://www.plm.automation.siemens.com/en_us/products/tecnomatix/robotics_automation/index.shtml. Accessed 3 February 2012

  16. Siemens (2011). NX Motion Simulation-RecurDyn: Simulate complex motion behavior. Available from http://www.plm.automation.siemens.com/en_us/Images/10659_tcm1023-4422.pdf. Accessed 3 February 2012

  17. Aleotti J, Caselli S, Reggiani M (2004) Leveraging on a virtual environment for robot programming by demonstration. Robot Auton Syst 47(2–3):153–161

    Article  Google Scholar 

  18. Aleotti J, Caselli S (2006) Robust trajectory learning and approximation for robot programming by demonstration. Robot Auton Syst 54(5):409–413

    Article  Google Scholar 

  19. Yanagihara Y, Kakizaki T, Arakawa K, Isoda Y (1998) A multimodal teaching advisor for sensor-enhanced robotic systems in manufacturing. Robot Comput Integr Manuf 14(4):263–273

    Article  Google Scholar 

  20. Iba S, Paredis CJJ, Khosla PK (2005) Interactive multimodal robot programming. Int J Robot Res 24(1):83–104

    Article  Google Scholar 

  21. Voliotis SD (1992) Orientation planning in continuous path applications for wrist partitioned manipulators. IEE Proc Contr Theor Appl 139(6):495–502

    Article  MATH  Google Scholar 

  22. Zhou L, Wang JF, Lin T, Chen SB (2007) Planning the torch orientation of planar lap joint in robotic welding. Robotic Welding, Intelligence and Automation (Lecture Notes in Control and Information Sciences) 362:145–151

    Article  Google Scholar 

  23. Chou WS, You L, Wang TM (2007) Automatic path planning for welding robot based on reconstructed surface model. Robotic Welding, Intelligence and Automation (Lecture Notes in Control and Information Sciences) 362:153–161

    Article  Google Scholar 

  24. He X, Chen Y (2009) Haptic-aided robot path planning based on virtual tele-operation. Robot Comput Integr Manuf 25(4–5):792–803

    Article  Google Scholar 

  25. Ong SK, Yuan ML, Nee AYC (2008) Augmented reality applications in manufacturing: a survey. Int J Prod Res 46(10):2707–2742

    Article  MATH  Google Scholar 

  26. Chou W, Wang T, Zhang Y (2004). Augmented reality based preoperative planning for robot assisted tele-neurosurgery. In: Proceedings of the IEEE International Conference on Systems, Man and Cybernetics, Hague, Netherlands, 10–13 October, pp. 2901–2906

  27. Craig JJ (2005) Introduction to robotics, mechanics and control. Pearson Education Inc., New York

    Google Scholar 

  28. Boyd S, Vandenberghe L (2004) Convex optimization. University Press, Cambridge

    MATH  Google Scholar 

  29. Verscheure D, Diehl M, De Schutter J, Swevers J (2009). On-line time-optimal path tracking for robots. In: Proceedings of the IEEE International Conference of Robotics and Automation. Kobe, Japan, 12–17 May, pp. 599–605

  30. Fang HC, Ong SK, Nee AYC (2012) Interactive robot trajectory planning and simulation using augmented reality. Robot Comput Integr Manuf 28(2):227–237

    Article  Google Scholar 

  31. ROBOOP (2009). http://www.cours.polymtl.ca/roboop. Accessed 3 February 2012

  32. Zhang W, Ma X, Cui L, Chen Q (2008). 3 points calibration method of part coordinates for arc welding robot. In: Proceedings of the International Conference Intelligent Robotics and Applications, Wuhan, China, 15–17 October, pp. 216–224

  33. Tsai MJ, Stone DJ (2009) Inverse velocity analysis for line guidance five-axis robots. Robot Comput Integr Manuf 25(4–5):736–745

    Article  Google Scholar 

  34. Pashkevich A (1997) Real-time inverse kinematics for robots with offset and reduced wrist. Control Eng Pract 5(10):1443–1450

    Article  Google Scholar 

  35. V-COLLIDE (1997). http://gamma.cs.unc.edu/V-COLLIDE/. Accessed 3 February 2012

  36. Gnuplot (2012). http://www.gnuplot.info. Accessed 3 February 2012.

  37. Constantinescu D, Croft EA (2000) Smooth and time-optimal trajectory planning for industrial manipulators along specified paths. J Robot Syst 17(5):233–249

    Article  MATH  Google Scholar 

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Authors and Affiliations

  1. Mechanical Engineering Department, Faculty of Engineering, National University of Singapore, 9 Engineering Drive 1, Singapore, 117576, Singapore

    H. C. Fang, S. K. Ong & A. Y. C. Nee

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  1. H. C. Fang
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  2. S. K. Ong
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  3. A. Y. C. Nee
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Correspondence to S. K. Ong.

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Fang, H.C., Ong, S.K. & Nee, A.Y.C. Orientation planning of robot end-effector using augmented reality. Int J Adv Manuf Technol 67, 2033–2049 (2013). https://doi.org/10.1007/s00170-012-4629-7

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  • DOI: https://doi.org/10.1007/s00170-012-4629-7

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