Architectural design of an Autonomous Decentralized System for controlling heterogeneous function multi-robots

This paper presents the architectural design of an Autonomous Decentralized System (ADS) for controlling heterogeneous function multi-robots which are belong to Wheeled Mobile Robots (WMRs). The heterogeneous function multi-robots are fully automated vehicles that are able to transport goods within varies functions in a complex environment. To cope with new and future system requirements such as flexibility and openness, we have applied a distributed planning system for developing decentralized control architecture for multi-robots system. In this paper, we give an overview of the software architecture of ADS and we zoom in on two specific concern: Self-generated action sequence and function complement. We discuss the evaluation of the software architecture and test results obtained from realistic simulations and an experiment system that we have developed.

[1]  Ling Qiu,et al.  Scheduling and routing algorithms for AGVs: A survey , 2002 .

[2]  Martial Hebert,et al.  A behavior-based system for off-road navigation , 1994, IEEE Trans. Robotics Autom..

[3]  Juan López Coronado,et al.  A real-time, unsupervised neural network for the low-level control of a mobile robot in a nonstationary environment , 1995, Neural Networks.

[4]  P. Fiorini,et al.  Motion planning in dynamic environments using the relative velocity paradigm , 1993, [1993] Proceedings IEEE International Conference on Robotics and Automation.

[5]  Stephen C. Daniels.  Real Time Conflict Resolution in Automated Guided Vehicle Scheduling , 1988 .

[6]  Nils J. Nilsson,et al.  A Formal Basis for the Heuristic Determination of Minimum Cost Paths , 1968, IEEE Trans. Syst. Sci. Cybern..

[7]  Satoshi Hoshino,et al.  Design of an AGV Transportation System by Considering Management Model in an ACT , 2006, IAS.

[8]  Antonio Bicchi,et al.  Decentralized Cooperative Conflict Resolution for Multiple Nonholonomic Vehicles , 2005 .

[9]  Debasish Ghose,et al.  Obstacle avoidance in a dynamic environment: a collision cone approach , 1998, IEEE Trans. Syst. Man Cybern. Part A.

[10]  Rick Kazman,et al.  Evaluating Software Architectures: Methods and Case Studies , 2001 .

[11]  Chang Wan Kim,et al.  Operational control of a bidirectional automated guided vehicle system , 1993 .

[12]  Hanan Samet,et al.  A hierarchical strategy for path planning among moving obstacles [mobile robot] , 1989, IEEE Trans. Robotics Autom..

[13]  Munindar P. Singh,et al.  Modeling exceptions via commitment protocols , 2005, AAMAS '05.

[14]  David G Lindeijer.  Controlling Automated Traffic Agents , 2003 .

[15]  J. K. Rosenblatt,et al.  A fine-grained alternative to the subsumption architecture for mobile robot control , 1989, International 1989 Joint Conference on Neural Networks.