Flexible Modeling And Simulation Architecture For Haptic Control Of Maritime Cranes And Robotic Arm

This paper introduces a modular prototyping system architecture that allows for the modeling, simulation and control of different maritime cranes or robotic arms with different kinematic structures and degrees of freedom using the Bond Graph Method. The resulting models are simulated in a virtual environment and controlled using the same input haptic device, which also provides the user with a valuable force feedback. The arm joint angles can be calculated at runtime according to the specific model of the robot to be controlled. The idea is to develop a library of crane beams, joints and actuator models that can be used as modules for simulating different cranes. The base module of this architecture is the crane beam model. Using different joint modules to connect several such models, different crane prototypes can be easily built. The library also includes a simplified model of a vessel to which the crane models can be connected in order to get a complete model. Related simulations were carried out using the so-called 20-sim simulator to validate efficiency and flexibility of the proposed architecture. In particular, a two-beam crane model connected to a simplified vessel model was implemented. To control the arm, an omega.7 from Force Dimension was used as an input haptic device.

[1]  Ronald Lumia,et al.  An approach to minimize robotics system development and integration time , 1997, Proceedings of International Conference on Robotics and Automation.

[2]  Dean Karnopp,et al.  System Dynamics: Modeling, Simulation, and Control of Mechatronic Systems , 1999 .

[3]  Jianqiang Yi,et al.  Anti-swing and positioning control of overhead traveling crane , 2003, Inf. Sci..

[4]  William Leithead,et al.  Semi-autonomous control of offshore cranes , 2007 .

[5]  H. Straky,et al.  1st IFAC-Conference on Mechatronic Systems , 2001 .

[6]  Jan F. Broenink,et al.  20-SIM software for hierarchical bond-graph/block-diagram models , 1999, Simul. Pract. Theory.

[7]  Leonimer Flavio de Melo,et al.  Virtual simulator with mobile robot rapid prototyping for navigation systems , 2009, 2009 International Conference on Information and Automation.

[8]  John J. Craig,et al.  Introduction to Robotics Mechanics and Control , 1986 .

[9]  A. Singla,et al.  Some aspects in the bond graph modelling of robotic manipulators: angular velocities from symbolic manipulation of rotation matrices , 2003, TENCON 2003. Conference on Convergent Technologies for Asia-Pacific Region.

[10]  Eilif Pedersen.  Rotordynamics and bond graphs: basic models , 2009 .

[11]  Shin-Min Song,et al.  An efficient method for inverse dynamics of manipulators based on the virtual work principle , 1993, J. Field Robotics.

[12]  Dean Karnopp,et al.  An approach to derivative causality in bond graph models of mechanical systems , 1992 .

[13]  Francis L. Merat,et al.  Introduction to robotics: Mechanics and control , 1987, IEEE J. Robotics Autom..

[14]  Ross R. Allen,et al.  Multiport representation of inertia properties of kinematic mechanisms , 1979 .

[15]  Eilif Pedersen,et al.  Bond Graph Modeling of Marine Vehicle Dynamics , 2012 .

[16]  Sergio Junco,et al.  Dynamics Of Multibody Systems With Bond Graphs. , 2007 .

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

[18]  R. Rosenberg,et al.  System Dynamics: Modeling and Simulation of Mechatronic Systems , 2006 .

[19]  Christian Fagereng,et al.  Mathematical Modeling for Marine Crane Operations , 2011 .

[20]  A. Hellrand,et al.  Crane Control System With Active Heave Compensation and Constant Tension Modes Onboard the Vessel Stena Wel/servicer , 1990 .