Agent-based distributed architecture for mobile robot control

Mobile robots are physical agents that move and interact continuously while embedded in a dynamic environment. Communications can be one of the most difficult parts of building robot architecture because of the increasing complexity of sensor and actuator hardware, and the interaction between intelligent features and real-time constraints. Currently, hybrid architectures offer the most widespread solutions for controlling intelligent mobile robots. This paper deals with the communications framework necessary to design and implement these architectures. The main goal of this work is to design a modular and portable architecture that allows the development of robot control systems. A multi-level and distributed architecture based on the reactive/deliberative paradigm is presented. Its main components are mobile software agents that interact through a distributed blackboard communications framework. These agents can be run on onboard processors, as well as on fixed workstations depending on their real-time restrictions. The presented control architecture has been tested in a real mobile robot and results demonstrate the effectiveness of distributing software agents to guarantee hard real-time execution.

[1]  Davide Brugali Software Engineering for Experimental Robotics, Workshop on Principles and Practice of Software Development in Robotics, PPSDR@ICRA 2005, Barcelona, Spain, April 18, 2005 , 2007, PPSDR@ICRA.

[2]  B. K. Panigrahi,et al.  ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE , 2010 .

[3]  Hermann Kopetz,et al.  Temporal firewalls in large distributed real-time systems , 1997, Proceedings of the Sixth IEEE Computer Society Workshop on Future Trends of Distributed Computing Systems.

[4]  Anders Orebäck,et al.  Evaluation of Architectures for Mobile Robotics , 2003, Auton. Robots.

[5]  V. Jagannathan,et al.  Blackboard Architectures and Applications , 1989 .

[6]  Alfons Crespo,et al.  Behaviour Selection in the YAIR Architecture , 1997 .

[7]  Ronald C. Arkin,et al.  An Behavior-based Robotics , 1998 .

[8]  T. Mexia,et al.  Author ' s personal copy , 2009 .

[9]  James S. Albus,et al.  4D/RCS: a reference model architecture for intelligent unmanned ground vehicles , 2002, SPIE Defense + Commercial Sensing.

[10]  Mohamed Fayad,et al.  Distributed computing in robotics and automation , 2002, IEEE Trans. Robotics Autom..

[11]  John-Jules Ch. Meyer Agent Technology , 2008, Wiley Encyclopedia of Computer Science and Engineering.

[12]  Robert W. Brennan,et al.  An agent-based approach to reconfiguration of real-time distributed control systems , 2002, IEEE Trans. Robotics Autom..

[13]  Danny B. Lange,et al.  Seven good reasons for mobile agents , 1999, CACM.

[14]  Christian Schlegel,et al.  Communication Patterns as Key towards Component-Based Robotics , 2006 .

[15]  Robin R. Murphy,et al.  Introduction to AI Robotics , 2000 .

[16]  Kurt Konolige,et al.  The saphira architecture for autonomous mobile robots , 1998 .

[17]  Erann Gat,et al.  Experiences with an architecture for intelligent, reactive agents , 1997, J. Exp. Theor. Artif. Intell..

[18]  Alexei Makarenko,et al.  Orca: A Component Model and Repository , 2005, PPSDR@ICRA.

[19]  Jay W. Gowdy A Qualitative Comparison of Interprocess Communications Toolkits for Robotics , 2000 .

[20]  Hichem Sahli,et al.  CoRoBa, a Multi Mobile Robot Control and Simulation Framework , 2006 .

[21]  Alex M. Andrew,et al.  Artificial Intelligence and Mobile Robots , 1999 .

[22]  Nils J. Nilsson,et al.  Principles of Artificial Intelligence , 1980, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[23]  Ronald C. Arkin,et al.  Integrating behavioral, perceptual, and world knowledge in reactive navigation , 1990, Robotics Auton. Syst..

[24]  Rodney A. Brooks,et al.  A Robust Layered Control Syste For A Mobile Robot , 2022 .

[25]  G. Benet,et al.  An architecture to control mobile robots by means of code delegation and multi-agent systems , 2004 .

[26]  Michael A. Arbib,et al.  The handbook of brain theory and neural networks , 1995, A Bradford book.

[27]  Rachid Alami,et al.  An Architecture for Autonomy , 1998, Int. J. Robotics Res..

[28]  Antonio Visioli,et al.  Gain Scheduling for Hybrid Force/Velocity Control in Contour Tracking Task , 2006 .

[29]  Alfons Crespo,et al.  Flexible real-time mobile robotic architecture based on behavioural models , 2001 .

[30]  Alexei Makarenko,et al.  Towards component-based robotics , 2005, 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[31]  Andy J. Wellings,et al.  Analysing real-time communications: controller area network (CAN) , 1994, 1994 Proceedings Real-Time Systems Symposium.

[32]  G. Benet,et al.  Communications structure for sensory data in mobile robots , 2002 .