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Putting the turing into manufacturing: recent developments in algorithmic automation

Published:17 June 2013Publication History

ABSTRACT

As global labor costs increase and product life cycles decrease, there is renewed interest in research in automated manufacturing systems that can be reliably and rapidly configured. Inspired by Turing's abstractions for computing, Algorithmic Automation explores mathematical abstractions and algorithms that allow the functionality of assembly lines and manufacturing automation systems to be designed independent of their underlying implementations. Abstractions based on minimal sets of geometric primitives can provide the foundation for formal specification, analysis, design, optimization, and verification. Algorithmic Automation is characterized by: (1) formal specification of sets of admissible inputs (eg, polyhedra) and operations (eg, parallel-jaw grasps), (2) complete algorithms that compute all solutions or terminate with a report that no solution exists, and (3) bounds on complexity as a function of input size. This extended abstract summarizes selected results and open problems.

References

  1. P. K. Agarwal, A. D. Collins, and J. L. Harer. Minimal trap design. In IEEE International Conference on Robotics and Automation, volume 3. IEEE, 2001.Google ScholarGoogle ScholarCross RefCross Ref
  2. R.-P. Berretty, K. Goldberg, L. Cheung, M. H. Overmars, G. Smith, and A. F. van der Stappen. Trap design for vibratory part feeders. International Journal of Robotics Research, 20(11), November 2001.Google ScholarGoogle ScholarCross RefCross Ref
  3. A. Bicchi and V. Kumar. Robotic grasping and contact: A review. In Robotics and Automation, 2000. Proceedings. ICRA'00. IEEE International Conference on, volume 1, pages 348--353. IEEE, 2000.Google ScholarGoogle ScholarCross RefCross Ref
  4. K.-F. Bohringer, V. Bhatt, B. R. Donald, and K. Goldberg. Algorithms for sensorless manipulation using a vibrating surface. Algorithmica, 26(3), 2000.Google ScholarGoogle Scholar
  5. R. C. Brost and K. Y. Goldberg. A complete algorithm for designing planar fixtures using modular components. IEEE Transactions on Robotics and Automation, 12(1):31--46, February 1996.Google ScholarGoogle ScholarCross RefCross Ref
  6. J. F. Canny and K. Y. Goldberg. Risc for industrial robots: Recent results and open problems. In IEEE Conference on Robotics and Automation, May 1994.Google ScholarGoogle Scholar
  7. J. Chen, K. Goldberg, M. H. Overmars, D. Halperin, K. F. Böhringer, and Y. Zhuang. Computing tolerance parameters for fixturing and feeding. Assembly Automation, 22(2):163--172, 2002.Google ScholarGoogle ScholarCross RefCross Ref
  8. Y.-B. Chen and D. Ierardi. The complexity of oblivious plans for orienting and distinguishing polygonal parts. Algorithmica, 14(5):367--397, 1995.Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. J.-S. Cheong, A. F. Van Der Stappen, K. Goldberg, M. H. Overmars, and E. Rimon. Immobilizing hinged polygons. International Journal of Computational Geometry & Applications, 17(01):45--69, 2007.Google ScholarGoogle ScholarCross RefCross Ref
  10. A. D. Christiansen and K. Y. Goldberg. Comparing two algorithms for programming robots in stochastic environments. Robotica, 13(6), 1995.Google ScholarGoogle Scholar
  11. D. Eppstein. Reset sequences for monotonic automata. SIAM Journal on Computing, 19(3):500--510, 1990. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. E. Fogel and D. Halperin. Polyhedral assembly partitioning with infinite translations or the importance of being exact. Trans. on Automation Science and Engineering (T-ASE), 10(2), 2013.Google ScholarGoogle Scholar
  13. O. C. Goemans, K. Goldberg, and A. F. van der Stappen. Blades: A new class of geometric primitives for feeding 3d parts on vibratory tracks. In IEEE Int'l Conf. on Robotics and Automation, 2006.Google ScholarGoogle Scholar
  14. K. Y. Goldberg. Orienting polygonal parts without sensors. Algorithmica, 10(3):201--225, August 1993.Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. K. Y. Goldberg and M. L. Furst. Low friction gripper, Mar. 24 1992. US Patent 5,098,145.Google ScholarGoogle Scholar
  16. K. Y. Goldberg and B. Kehoe. Cloud robotics and automation: A survey of related work. EECS Department, University of California, Berkeley, Tech. Rep. UCB/EECS-2013--5, 2013.Google ScholarGoogle Scholar
  17. K. Gopalakrishnan, K. Goldberg, G. M. Bone, M. J. Zaluzec, R. Koganti, R. Pearson, and P. A. Deneszczuk. Unilateral fixtures for sheet metal parts with holes. IEEE Transactions on Automation Science and Engineering, 1(2):110--120, October 2004.Google ScholarGoogle ScholarCross RefCross Ref
  18. K. Gopalakrishnan, K. Goldberg, et al. D-space and deform closure grasps of deformable parts. International Journal of Robotics Research, 24(11), November 2005.Google ScholarGoogle ScholarCross RefCross Ref
  19. B. Kehoe, D. Berenson, and K. Goldberg. Estimating part tolerance bounds based on adaptive cloud-based grasp planning with slip. In IEEE Conference on Automation Science and Engineering, August 2012.Google ScholarGoogle ScholarCross RefCross Ref
  20. B. Kehoe, A. Matsukawa, S. Candido, J. Kuffner, and K. Goldberg. Cloud-based robot grasping with the google object recognition engine. In IEEE Int'l Conf. on Robotics and Automation, 2013.Google ScholarGoogle Scholar
  21. J.-C. Latombe. Robot algorithms. In Proceedings of the First Workshop on Algorithmic Foundations of Robotics (WAFR), pages 1--18. AK Peters, Ltd., 1995. Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. V. Milenkovic, E. Sacks, and S. Trac. Planar shape manipulation using approximate geometric primitives. In Proceedings of the Tenth Workshop on Algorithmic Foundations of Robotics (WAFR). Springer, 2012.Google ScholarGoogle Scholar
  23. B. Mishra. Workholding-analysis and planning. In Intelligent Robots and Systems' 91.'Intelligence for Mechanical Systems, Proceedings IROS'91. IEEE/RSJ International Workshop on, pages 53--57. IEEE, 1991.Google ScholarGoogle Scholar
  24. B. Mishra, J. T. Schwartz, and M. Sharir. On the existence and synthesis of multifinger positive grips. Algorithmica, 2(1--4):541--558, 1987.Google ScholarGoogle Scholar
  25. B. Natarajan. An algorithmic approach to the automated design of parts orienters. In Foundations of Computer Science, 1986., 27th Annual Symposium on, pages 132--142. IEEE, 1986. Google ScholarGoogle ScholarDigital LibraryDigital Library
  26. Y. Ostrovsky-Berman and L. Joskowicz. Tolerance envelopes of planar mechanical parts. In 9th Symposium on Solid modeling and Applications. ACM, 2004. Google ScholarGoogle ScholarDigital LibraryDigital Library
  27. E. Plaku, K. E. Bekris, and L. E. Kavraki. Oops for motion planning: An online, open-source, programming system. In IEEE International Conference on Robotics and Automation. IEEE, 2007.Google ScholarGoogle ScholarCross RefCross Ref
  28. R. Platt, L. Kaelbling, T. Lozano-Perez, and R. Tedrake. Simultaneous localization and grasping as a belief space control problem. In International Symposium on Robotics Research, volume 2, 2011.Google ScholarGoogle Scholar
  29. M. Quigley, K. Conley, B. Gerkey, J. Faust, T. Foote, J. Leibs, R. Wheeler, and A. Y. Ng. Ros: an open-source robot operating system. In International Conf. on Robotics and Automation Workshop on Open Source Software. IEEE, 2009.Google ScholarGoogle Scholar
  30. A. Rao and K. Goldberg. Manipulating algebraic parts in the plane. IEEE Transactions on Robotics and Automation, 11(4), August 1995.Google ScholarGoogle ScholarCross RefCross Ref
  31. A. A. Requicha. Toward a theory of geometric tolerancing. The International Journal of Robotics Research, 2(4):45--60, 1983.Google ScholarGoogle ScholarCross RefCross Ref
  32. A. A. Requicha. Mathematical definition of tolerance specifications. Manufacturing Review, 6:269--269, 1993.Google ScholarGoogle Scholar
  33. E. Rimon and A. Blake. Caging planar bodies by one-parameter two-fingered gripping systems. The International Journal of Robotics Research, 18(3):299--318, 1999.Google ScholarGoogle ScholarCross RefCross Ref
  34. E. Rimon and J. W. Burdick. New bounds on the number of frictionless fingers requied to immobilize. Journal of Robotic Systems, 12(6):433--451, 1995.Google ScholarGoogle ScholarCross RefCross Ref
  35. E. Rimon and A. F. van der Stappen. Immobilizing 2-d serial chains in form-closure grasps. Robotics, IEEE Transactions on, 28(1):32--43, 2012. Google ScholarGoogle ScholarDigital LibraryDigital Library
  36. A. Rodriguez, M. T. Mason, and S. Ferry. From caging to grasping. The International Journal of Robotics Research, 31(7):886--900, 2012. Google ScholarGoogle ScholarDigital LibraryDigital Library
  37. J. D. Schulman, K. Goldberg, and P. Abbeel. Grasping and fixturing as submodular coverage problems. In International Symposium on Robotics Research, September 2011.Google ScholarGoogle Scholar
  38. G. Smith, E. Lee, K. Goldberg, K. Bohringer, and J. Craig. Computing parallel-jaw grip points. In IEEE International Conference on Robotics and Automation, May 1999.Google ScholarGoogle Scholar
  39. R. H. Taylor, M. T. Mason, and K. Y. Goldberg. Sensor-based manipulation planning as a game with nature. In 4th International Symposium on Robotics Research. MIT Press, 1988. Google ScholarGoogle ScholarDigital LibraryDigital Library
  40. M. Vahedi and A. F. van der Stappen. Caging polygons with two and three fingers. The International Journal of Robotics Research, 27(11--12):1308--1324, 2008.Google ScholarGoogle Scholar
  41. A. F. van der Stappen. Immobilization: Analysis, existence, and output-sensitive synthesis a. frank van der stappen. In Dimacs Workshop Computer Aided Design and Manufacturing, October, volume 67, page 165. Amer Mathematical Society, 2003.Google ScholarGoogle Scholar
  42. A. F. van der Stappen, K. Goldberg, and M. H. Overmars. Geometric eccentricity and the complexity of manipulation plans. Algorithmica, 26(3):494--514, March 2000.Google ScholarGoogle Scholar
  43. C. Wentink, A. Stappen, and M. H. Overmars. Fixture design with edge-fixels. In Intelligent Robots: Sensing, Modeling and Planning {Dagstuhl Workshop, September 1--6, 1996}, pages 269--286. World Scientific Press, 1996. Google ScholarGoogle ScholarDigital LibraryDigital Library
  44. J. Wiegley, K. Goldberg, M. Peshkin, and M. Brokowski. A complete algorithm for designing passive fences to orient parts. Assembly Automation, 17(2):129--136, 1997.Google ScholarGoogle ScholarCross RefCross Ref
  45. Y. Zhuang and K. Goldberg. On the existence of modular fixtures. International Journal of Robotics Research, 15(5), December 1996. Google ScholarGoogle ScholarDigital LibraryDigital Library

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          cover image ACM Conferences
          SoCG '13: Proceedings of the twenty-ninth annual symposium on Computational geometry
          June 2013
          472 pages
          ISBN:9781450320313
          DOI:10.1145/2462356

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          Publication History

          • Published: 17 June 2013

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          SoCG '13 Paper Acceptance Rate48of137submissions,35%Overall Acceptance Rate625of1,685submissions,37%

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