A Tool Set for Modeling and Simulation of Robotic Workcells

Robotic systems are a notable example of the class of reactive systems in which design complexity faces not only timing constraints and correct ordering in execution, but also spatial relationships and dynamic evolution of robotic units. Simulation of agents in a 3D environment is a way for getting a better understanding of system behavior as well as detecting possible hazardous conditions concerning event sequencing and timing, along with their relations with spatial constraints. In this paper, a formal high-level control model based on Time Petri Nets is used to capture robot behavior and to drive animation in the virtual 3D environment. A rich set of tools has been developed to allow assembly of virtual robots, their composition into a virtual workcell and the definition of the control model itself.

[1]  Tadao Murata,et al.  Petri nets: Properties, analysis and applications , 1989, Proc. IEEE.

[2]  Wyatt S. Newman,et al.  Virtual testing of agile manufacturing software using 3D graphical simulation , 1997, Proceedings of International Conference on Robotics and Automation.

[3]  Stewart Robinson,et al.  Simulation model verification and validation: increasing the users' confidence , 1997, WSC '97.

[4]  Klas Nilsson,et al.  On the scalability of visualization in manufacturing , 1999, 1999 7th IEEE International Conference on Emerging Technologies and Factory Automation. Proceedings ETFA '99 (Cat. No.99TH8467).

[5]  Seth Hutchinson,et al.  Coordinating the motions of multiple robots with specified trajectories , 2002, Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292).

[6]  P. Merlin,et al.  Recoverability of Communication Protocols - Implications of a Theoretical Study , 1976, IEEE Transactions on Communications.

[7]  L. Muñoz,et al.  Virtual Laboratory , 2002 .

[8]  Andreas Speck,et al.  RoboSiM: Java 3D robot visualization , 1999, IECON'99. Conference Proceedings. 25th Annual Conference of the IEEE Industrial Electronics Society (Cat. No.99CH37029).

[9]  Krithi Ramamritham,et al.  Scheduling algorithms and operating systems support for real-time systems , 1994, Proc. IEEE.

[10]  Enrico Vicario,et al.  Construction workers instruction and training , 1999, Proceedings IEEE International Conference on Multimedia Computing and Systems.

[11]  Enrico Vicario,et al.  Static Analysis and Dynamic Steering of Time-Dependent Systems , 2001, IEEE Trans. Software Eng..

[12]  Matthew W. Rohrer.  Seeing is believing: the importance of visualization in manufacturing simulation , 2000, 2000 Winter Simulation Conference Proceedings (Cat. No.00CH37165).

[13]  Alberto Del Bimbo,et al.  Visual Programming of Virtual Worlds Animation , 1996, IEEE Multim..

[14]  Bojan Cukic,et al.  Virtual environment modeling for requirements validation of high consequence systems , 2001, Proceedings Fifth IEEE International Symposium on Requirements Engineering.

[15]  Yiannis E. Papelis,et al.  HCSM: a framework for behavior and scenario control in virtual environments , 1995, TOMC.