Towards Coordinated Precision Assembly with Robot Teams

详细信息    查看全文

• 关键词：Robotic assembly ; Robotic manufacturing ; Robot teams ; Distributed control ; Precision assembly ; Perception
• 刊名：Springer Tracts in Advanced Robotics
• 出版年：2016
• 出版时间：2016
• 年：2016
• 卷：109
• 期：1
• 页码：655-669
• 全文大小：503 KB
• 参考文献：1.Allen, P.K.: Integrating vision and touch for object recognition tasks. Int. J. Robot. Res. 7(6), 15–33 (1988)CrossRef
  2.Bourne, D.: My boss the robot. Sci. Am. 308(5), 38–41 (2013)CrossRef
  3.Burridge, R.R., Rizzi, A.A., Koditschek, D.E.: Sequential composition of dynamically dexterous robot behaviors. Int. J. Robot. Res. 18(6), 534–555 (1999)CrossRef
  4.Choi, C., Christensen, H.I.: Robust 3D visual tracking using particle filtering on the Special Euclidean group: a combined approach of keypoint and edge features. Int. J. Robot. Res. 31(4), 498–519 (2012)CrossRef
  5.Choi, C., Christensen, H.I.: RGB-D object tracking: a particle filter approach on GPU. In: Proceedings of the IEEE International Conference on Intelligent Robots and Systems, pp. 1084–1091 (2013)
  6.Collet, A., Martinez, M., Srinivasa, S.S.: The moped framework: object recognition and pose estimation for manipulation. Int. J. Robot. Res. 30(10), 1284–1306 (2011)CrossRef
  7.Conner, D.C., Rizzi, A.A., Choset, H.: Composition of local potential functions for global robot control and navigation. In: Proceedings of the IEEE International Conference on Intelligent Robots and Systems, vol. 4, pp. 3546–3551. IEEE (2003)
  8.Das, A.K., Fierro, R., Kumar, V., Ostrowski, J.P., Spletzer, J., Taylor, C.J.: A vision-based formation control framework. IEEE Trans. Robot. Autom. 18(5), 813–825 (2002)CrossRef
  9.Desai, J.P., Kumar, V.: Motion planning for cooperating mobile manipulators. J. Robot. Syst. 16(10), 557–579 (1999)MATH CrossRef
  10.Ilonen, J., Bohg, J., Kyrki, V.: Fusing visual and tactile sensing for 3-D object reconstruction while grasping. In: Proceedings of the IEEE International Conference on Robotics and Automation, pp. 3547–3554 (2013)
  11.Inoue, H.: Force feedback in precise assembly tasks. Technical report, DTIC Document (1974)
  12.Khatib, O., Yokoi, K., Chang, K., Ruspini, D., Holmberg, R., Casal, A.: Coordination and decentralized cooperation of multiple mobile manipulators. J. Robot. Syst. 13(11), 755–764 (1996)CrossRef
  13.Klein, G., Drummond, T.: Tightly integrated sensor fusion for robust visual tracking. Image Vis. Comput. 22(10), 769–776 (2004)CrossRef
  14.Lenz, C., Nair, S., Rickert, M., Knoll, A., Rosel, W., Gast, J., Bannat, A., Wallhoff, F.: Joint-action for humans and industrial robots for assembly tasks. In: RO-MAN, pp. 130–135 (2008)
  15.Li, Z., Ge, S.S., Wang, Z.: Robust adaptive control of coordinated multiple mobile manipulators. Mechatronics 18(5–6), 239–250 (2008)CrossRef
  16.Lozano-Perez, T., Mason, M.T., Taylor, R.H.: Automatic synthesis of fine-motion strategies for robots. Int. J. Robot. Res. 3(1), 3–24 (1984)CrossRef
  17.Mason, M.T.: Compliance and force control for computer controlled manipulators. IEEE Trans. Syst. Man Cybern. 11(6), 418–432 (1981)CrossRef
  18.Mason, M.T.: The mechanics of manipulation. In: Proceedings of the IEEE International Conference on Robotics and Automation, vol. 2, pp. 544–548. IEEE (1985)
  19.Raibert, M.H., Craig, J.J.: Hybrid position/force control of manipulators. J. Dyn. Syst. Meas. Control 103(2), 126–133 (1981)CrossRef
  20.Reinhart, G., Zaidan, S.: A generic framework for workpiece-based programming of cooperating industrial robots. In: ICMA, pp. 37–42 (2009)
  21.Rusu, R.B., Bradski, G., Thibaux, R., Hsu, J.: Fast 3d recognition and pose using the viewpoint feature histogram. In: IROS, pp. 2155–2162 (2010)
  22.Skotheim, Ø., Nygaard, J.O., Thielemann, J., Vollset, T.: A flexible 3d vision system based on structured light for in-line product inspection. Electr. Imaging 2008, 680505–680505 (2008)
  23.Sugar, T.G., Kumar, V.: Control of cooperating mobile manipulators. IEEE Trans. Robot. Autom. 18(1), 94–103 (2002)CrossRef
  24.Tedrake, R., Manchester, I.R., Tobenkin, M., Roberts, J.W.: Lqr-trees: feedback motion planning via sums-of-squares verification. Int. J. Robot. Res. 29(8), 1038–1052 (2010)CrossRef
  25.Yamashita, A., Arai, T., Ota, J., Asama, H.: Motion planning of multiple mobile robots for cooperative manipulation and transportation. IEEE Trans. Robot. Autom. 19(2), 223–237 (2003)
  
• 作者单位：Mehmet Dogar (6)
  Ross A. Knepper (6)
  Andrew Spielberg (6)
  Changhyun Choi (7)
  Henrik I. Christensen (7)
  Daniela Rus (6)
  
  6. Computer Science and Artificial Intelligence Lab, MIT, Cambridge, USA
  7. Institute for Robotics and Intelligent Machines, College of Computing, Georgia Tech, Atlanta, Georgia
  
• 丛书名：Experimental Robotics
• ISBN：978-3-319-23778-7
• 刊物类别：Engineering
• 刊物主题：Automation and Robotics
  Control Engineering
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1610-742X

文摘

We present a system in which a flexible team of robots coordinates to assemble large, complex, and diverse structures autonomously. Our system operates across a wide range of spatial scales and tolerances, using a hierarchical perception architecture. For the successful execution of very precise assembly operations under initial uncertainty, our system starts with high-field of view but low accuracy sensors, and gradually uses low field-of-view but high accuracy sensors. Our system also uses a failure detection and recovery system, integrated with this hierarchical perception architecture: upon losing track of a feature, our system retracts to using high-field of view systems to re-localize. Additionally, we contribute manipulation skills and tools necessary to assemble large structures with high precision. First, the team of robots coordinates to transport large assembly parts which are too heavy for a single robot to carry. Second, we develop a new tool which is capable of co-localizing holes and fasteners for robust insertion and fastening. We present real robot experiments where we measure the contribution of the hierarchical perception and failure recovery approach to the robustness of our system. We also present an extensive set of experiments where our robots successfully insert all 80 of the attempted fastener insertion operations.