Modeling & control of a meat-cutting robotic cell

In this paper, the modeling, simulation and control of a robotic meat cutting cell is described. A dual-arm system is used in the separation task, one arm cuts the meat along a deformable guide line while the second arm graps and pulls the meat to further increase the opening of the valley. The steps taken to model the cell in order to ensure a realistic interaction between the robots and the flexible object are outlined. A control scheme, using an external vision and force sensors, is proposed that copes with on-line object deformation. The proposed control scheme is validated using the simulator environment.

[1]  Wisama Khalil,et al.  A new geometric notation for open and closed-loop robots , 1986, Proceedings. 1986 IEEE International Conference on Robotics and Automation.

[2]  Vincenzo Lippiello,et al.  Robot Interaction Control Using Force and Vision , 2006, 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[3]  Eric Lemoine,et al.  Robotic cell with redundant architecture and force control: application to cutting and boning , 2010, 19th International Workshop on Robotics in Alpe-Adria-Danube Region (RAAD 2010).

[4]  Neville Hogan,et al.  Impedance Control: An Approach to Manipulation: Part II—Implementation , 1985 .

[5]  Allison M. Okamura,et al.  Modeling of Tool-Tissue Interactions for Computer-Based Surgical Simulation: A Literature Review , 2008, PRESENCE: Teleoperators and Virtual Environments.

[6]  Simon K. Warfield,et al.  On Extended Finite Element Method (XFEM) for Modelling of Organ Deformations Associated with Surgical Cuts , 2004, ISMS.

[7]  U. Ku,et al.  Endoscopic surgery training using virtual reality and deformable tissue simulation , 2000 .

[8]  P. Stergiopoulos,et al.  A framework for the haptic rendering of the human hand , 2003, 11th Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems, 2003. HAPTICS 2003. Proceedings..

[9]  Lars Hinrichsen.  Manufacturing technology in the Danish pig slaughter industry. , 2010, Meat science.

[10]  Rs Roel Pieters,et al.  Visual Servo Control , 2012 .

[11]  Patrick Rives,et al.  A new approach to visual servoing in robotics , 1992, IEEE Trans. Robotics Autom..

[12]  Neville Hogan,et al.  Impedance Control: An Approach to Manipulation , 1984, 1984 American Control Conference.

[13]  Sarah F. Frisken.  Using Linked Volumes to Model Object Collisions, Deformation, Cutting, Carving, and Joining , 1999, IEEE Trans. Vis. Comput. Graph..

[14]  Neville Hogan,et al.  Impedance Control: An Approach to Manipulation: Part III—Applications , 1985 .

[15]  P. Martinet,et al.  Image-based visual servoing of Gough-Stewart parallel manipulators using legs observation , 2006 .

[16]  G Purnell.  Robotic equipment in the meat industry. , 1998, Meat science.

[17]  Patrick Rives,et al.  A new approach to visual servoing in robotics , 1992, IEEE Trans. Robotics Autom..

[18]  François Chaumette,et al.  Visual servo control. I. Basic approaches , 2006, IEEE Robotics & Automation Magazine.

[19]  Minoru Asada,et al.  Adaptive hybrid control for visual and force servoing in an unknown environment , 1998, IEEE Robotics Autom. Mag..

[20]  Stephane Cotin,et al.  A hybrid elastic model for real-time cutting, deformations, and force feedback for surgery training and simulation , 1999, Proceedings Computer Animation 1999.

[21]  Stefano Carpin,et al.  Combining imitation and reinforcement learning to fold deformable planar objects , 2011, 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[22]  Oussama Khatib,et al.  A unified approach for motion and force control of robot manipulators: The operational space formulation , 1987, IEEE J. Robotics Autom..

[23]  Mariano Alcañiz Raya,et al.  Real-time deformable models for surgery simulation: a survey , 2005, Comput. Methods Programs Biomed..