Abstract
The work solves the problem of task and motion planning of a self-reconfigurable fixture system. A feasible solution is a key requirement for the viability of such systems, which have raised hopes of overcoming the deficiencies that more traditional fixtures are recognized to have in the dynamic conditions of modern manufacturing, with its increasing emphasis on flexibility, adaptability, and automation. The paper proposes an application-independent approach for the generation of a time-relevant action plan for the locomotion, reconfiguration, and positioning of two or more mobile robotic fixtures. The fixture agents need to provide local support for a large workpiece during machining. The path-planning problem is converted into a constraint satisfaction problem (CSP). The proposed approach is called Triple-CSP, as it applies an incremental state search to solve three hierarchical path-planning tasks for the three components of each mobile fixture agent: a supporting head, a mobile base, and a parallel manipulator. A final time-related trajectory (time scaling of actions) for the agents’ entire task execution is obtained. Thus, the planner takes into account all the relevant physical, geometrical, and time-related constraints.
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References
Menassa R, De Vries W (1991) Optimization methods applied to selecting support positions in fixture design. ASME J Eng Ind 113(4):412–418
Cai W, Hu S, Yuan J (1996) Deformable sheet metal fixturing: principles, algorithms, and simulations. J Manuf Sci Eng Trans ASME 118(3):318–324
Vallapuzha S, De Meter E, Choudhuri S, Khetan R (2002) An investigation of the effectiveness of fixture layout optimization methods. Int J Mach Tool Manuf 42(2):251–263
Sela M, Gaudry O, Dombre E, Benhabib B (1997) A reconfigurable modular fixturing system for thin-walled flexible objects. Int J Adv Manuf Technol 13(9):611–617
Shirinzadeh B, Tie Y (1995) Experimental investigation of the performance of a reconfigurable fixture system. Int J Adv Manuf Technol 10(5):330–341
Youcef-Toumi K, Liu W, Asada H (1988) Computer-aided analysis of reconfigurable fixtures and sheet metal parts for robotics drilling. Robot Comput Integr Manuf 4(3–4):387–393
Bi Z, Zhang W (2001) Flexible fixture design and automation: review, issues and future directions. Int J Prod Res 39(13):2867–2894
Kang Y, Rong Y, Yang J, Ma W (2002) Computer-aided fixture design verification. Assem Autom 22(4):350–359
Zhang WJ, van Luttervelt CA (2011) Toward a resilient manufacturing system. CIRP Ann Manuf Technol 60:469–472
Boyle I, Rong Y, Brown D (2011) A review and analysis of current computer-aided fixture design approaches. Robot Comput Integr Manuf 27(1):1–12
Molfino R, Zoppi M, Zlatanov D (2009) Reconfigurable swarm fixtures. In: REMAR 2009. Proceedings of the 2009 ASME/IFToMM international conference on reconfigurable mechanisms and robots, vol IEEE : CFP0943G-PRT, pp 730–735
de Leonardo Girard LM, Zoppi M, Li X, Zlatanov D, Molfino RM (2013) SwarmItFIX: a multi-robot-based reconfigurable fixture. Ind Robot Int J 40(4):320–328
Gonzalez-Rodriguez A, Gonzalez-Rodriguez A (2011) Collision-free motion planning and scheduling. Robot Comput Integr Manuf 27(3):657–665
DeMeter E (1998) Fast support layout optimization. Int J Mach Tool Manuf 38(10-11):1221–1239
Asante JN (2010) Effect of fixture compliance and cutting conditions on workpiece stability. Int J Adv Manuf Technol 48(1-4):33–43
Papastathis TN, Ratchev SM, Popov AA (2012) Dynamics model of active fixturing systems for thin-walled parts under moving loads. Int J Adv Manuf Technol 62(9-12):1233–1247
Rearick M, Hu S, Wu S (1993) Optimal fixture design for deformable sheet metal workpieces. Trans NAMRI/SME 21:407–412
Canny J (1993) Computing roadmaps of general semi-algebraic sets. Comput J 36(5):504–514
Choset H, Lynch K, Hutchinson S, Kantor G, Burgard W, Kavraki L, Thrun S (2005) Principles of robot motion: theory, algorithms, and implementations. MIT Press, Cambridge
LaValle S (2006) Planning algorithms. Cambridge University Press, Cambridge
Kavraki LE, Svestka P, Latombe J-C, Overmars MH (1996) Probabilistic roadmaps for path planning in high-dimensional configuration spaces. IEEE Trans Robot Autom 12(4):566– 580
Kuffner JJ, LaValle SM (2000) RRT-connect: an efficient approach to single-query path planning. In: IEEE international conference on robotics and automation. San Francisco, pp 995–1001
Jaillet L, Cortes J, Simeon T (2010) Sampling-based path planning on configuration-space costmaps. IEEE Trans Robot 26(4):635–646
Brock O, Khatib O (2002) Elastic strips: a framework for motion generation in human environments. Int J Robot Res 18(6):1031–1052
Latombe J-C (1991) Robot motion planning. Kluwer, Boston
Ratliff N, Zucker M, Bagnell JA, Srinivasa S (2009) Chomp: gradient optimization techniques for efficient motion planning. In: IEEE international conference on robotics and automation (ICRA), pp 489–494
Russel S, Norvig P (2002) Artificial intelligence. A modern approach. Prentice-Hall, Upper Saddle River
Brailsford SC, Potts CN, Smith BM (1999) Constraint satisfaction problems: algorithms and applications. Eur J Oper Res 119(3):557–581
Apt KR (2003) Principles of constraint programming. Cambridge University Press, Cambridge
Bartak R, Salido MA, Rossi F (2010) Constraint satisfaction techniques in planning and scheduling. J Intell Manuf 21(1):5–15
Sun Z, Zhang B, Cheng L, Zhang WJ (2011) Application of the redundant servomotor approach to design of path generator with dynamic performance improvement. Mech Mach Theory 46:1784–1795
Zieliński C, Kornuta T, Trojanek P, Winiarski T, Walecki M (2012) Specification of a robot-based reconfigurable fixture control system. In: Robot motion and control 2011. Lecture notes in control and information sciences, vol 422. Springer, London, pp 171–182
Neumann K-E (2008) Structure concept of Exechon PKM, Tech. Rep. 34, Exechon, Stockholm. exechonworld.com/document/200804/article34.htm Accessed 8 July 2013
Li X, Zoppi M, Molfino R, de Leonardo Girard LM (2011) Design of mobile base for a self-reconfigurable intelligent swarm fixture system. In: CLAWAR 2011. The 14th international conference on climbing and walking robots and the support technologies for mobile machines, Paris, 6-8 September 2011, pp 925-932
Zoppi M, Molfino R, Zlatanov D (2011) Bench and method for the support and manufacturing of parts with complex geometry. European Patent WO2011EP58992 20110531
Szynkiewicz W, Zielińska T, Kasprzak W (2010) Robotized machining of big work pieces: localization of supporting heads. Front Mech Eng China 5(4):357–369. http://springerlink.com/content/1673-3479/5/4/
Arzanpour S, Fung J, Mills JK, Cleghorn WL (2006) Flexible fixture design with applications to assembly of sheet metal automotive body parts. Assem Autom 26(2):143–153
Shen CH, Lin YT, Agapiou JS, Bandyopadhyay P (2006) Reconfigurable fixtures for automotive engine machining and assembly applications. In: Reconfigurable manufacturing systems and transformable factories. Springer, Berlin, pp 155–194
Bi Z, Lang S, Verner M, Orban P (2008) Development of reconfigurable machines. Int J Adv Manuf Technol 39(11):1227–1251
Jonsson M, Ossbahr G (2010) Aspects of reconfigurable and flexible fixtures. Prod Eng 4(4):333–339
Papastathis T, Bakker O, Ratchev S, Popov A (2012) Design methodology for mechatronic active fixtures with movable clamps. Procedia CIRP 3:323–328
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Kasprzak, W., Zlatanov, D., Szynkiewicz, W. et al. Task planning for cooperating self-reconfigurable mobile fixtures. Int J Adv Manuf Technol 69, 2555–2568 (2013). https://doi.org/10.1007/s00170-013-5185-5
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DOI: https://doi.org/10.1007/s00170-013-5185-5