Navigational Intelligence of an Autonomous Mobile Robot participating in an Agent Based Architecture co-ordinates


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Abstract


Developing a physical agent based structural design model through a mixed agents and designing the best realistic path for an autonomous mobile robot agents are one of the key area, which gains much attention to the researchers in this field of Robotics and Artificial Intelligence. This paper aim’s the study on navigational characteristic of an autonomous mobile robot agent by identifying the optimal path, based on agent based coordination. The key intent of this paper is to find a sub-optimal path for an autonomous mobile robot using master-subordinate architecture in an identified or unidentified environment based on agent’s navigation. The sub-optimal path is determined by a heuristics approach, called A Star (A*) algorithm. The communication control between the autonomous mobile robot agent and its server will be accomplished based on the open agent architecture, which will be treated as a master-subordinate architecture. The autonomous mobile robot agent use to communicate with its server to update the optimized path details, required to achieve its target position, in an optimized way. Research in the field of robotics is closely unified with simulation tools for numerous reasons. The simulation were conducted using a graphical user interface (GUI) based test-bed environment for robots, called MobileSim and the system efficiency was measured, via the generated simulation results.


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Keywords


Autonomous Mobile Robot Agent Co-Operation; Path Planning; Exploration; Handoff Negotiation; Heuristic Approach

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References


M.BalaSubramanian, Dr.K.Sudhagar, G.RajaRajeswari, “A Study on seamless information sharing between robots in identifying the optimal path: An agent based approach”, Proc. of Int. Conf. on Advances in Communication, Network, and Computing, Elseiver Publication, CNC,2014, INDIA

Sud, A., Andersen, E., Curtis, S., Lin, M., and Manocha, D. “Real-time path planning for virtual agents in dynamic environment,” Proc., IEEE Virtual Reality Conf., IEEE, New York, 91–98. (2007).

Ugur Gurela, Osman Parlaktunab, Hilal Ezercan Kayır, “Agent-based route planning for a mobile robot,” 5th International Advanced Technologies Symposium (IATS’09), May 13-15, 2009, Karabuk, Turkey

Godwin Raja Ebenezer, N., Saravanan, R., Ramabalan, S., Natarajan, R., Evolutionary optimum design for a task specified 6-link planar robot, (2014) International Review of Mechanical Engineering (IREME), 8 (1), pp. 36-51.

Kawamura, K., P. Nilas, K. Muguruma, J.A. Adams and C. Zhou, "An Agent-Based Architecture for an Adaptive Human-Robot Interface", Hawaii International Conference on System Sciences (HICSS-36), Big Island, Hawaii, January 6-9, 2003.

Zavlanos, M.M.; Pappas, G.J.;” Dynamic Assignment in Distributed Motion Planning with Local Coordination,” IEEE Transactions on Robotics Volume 24, Issue 1, Feb. 2008 Page(s):232-242 Digital Object Identifier 10.1109/TRO.2007.913992

Yan Meng, “Agent-based re-configurable architecture for real-time object tracking,” Journal of Real-Time Image Processing, 2009, Vol. 4: 339-351

Aboura, S.B., Omari, A., Meguenni, K.Z., Motion planning and control of hyper dynamic robot arm, (2014) International Review of Automatic Control (IREACO), 7 (1), pp. 82-89.

H. Omranpour, S. Shiry, “Reduced Search Space Algorithm for Simultaneous Localization and Mapping in Mobile Robots.” International Journal of Robotics and Automation (IJRA), Vol.1, No.1, March 2012, pp.49~63 ISSN: 2089-4872.

Lynne E. Parker. “Current state of the art in distributed autonomous mobile robotics.” In George Bekey Lynne E. Parker and Jacob Barhen, editors, Distributed Autonomous Robotic System 4, pages 3–12, October 2000.

Rushan, S.M.; Mehrandezh, M.; Paranjape, R.; “Localization of a team of heterogeneous robots for a distributed Sensing Task,” Electrical and Computer Engineering, 2006. CCECE '06. Canadian Conference on May 2006 Page(s):1522 – 1525 DOI 10.1109/CCECE.2006.277605

Lynne E.Parker, Path Planning and Motion coordination in Multiple Mobile Robot Teams, in Encyclopedia of Complexity and System Science, Springer,2009.

http://www.ai.sri.com/~oaa/

Ferber, J. (1999). “Multi-agent system, an introduction to distributed artificial intelligence,” Addison-Wesley/Pearson Education, Upper Saddle River, NJ.

Zhang, C., and Hammad, A. (2012). “Multiagent Approach for Real-Time Collision Avoidance and Path Replanning for Cranes” Journal of Computing in CIVIL Engineering, 26(2), 782-794.

http://www.ukessays.com/essays/information-technology/a-heterogeneous-networks-using-mobility-management-information-technology-essay.php

J.Ferber, Y.Demazeau, O.Gutknecht, Aladdin: ”A meta-model for the analysis and design of organizations in multi-agent systems,” Third International; Conference on Mulit Agent Systems, Paris, IEEE, 1998.

Ferber, J. (1999). “Multi-agent system, an introduction to distributed artificial intelligence,” Addison-Wesley/Pearson Education, Upper Saddle River, NJ.

D. L. Martin, A. J. Cheyer, and D. B. Moran, "The Open Agent Architecture: A framework for building distributed software systems," Applied Artificial Intelligence: An International Journal. Volume 13, Number 1-2, January-March 1999. pp 91-128

Adiline Macriga, Dr. P. Anandha Kumar, “Seamless Data Services for Real Time Communication in a Heterogeneous Networks using Network Tracking and Management,” (IJCSIS) International Journal of Computer Science and Information Security, Vol. 7, No. 3, March 2010

Y. Fang, “Tradeoff analysis for location update and paging in wireless networks,” in Proc. IEEE GLOBECOM, San Antonio, TX, Nov. 2001, pp. 1754–1758

Wenchao Ma, Yuguang Fang and Phone Lin, “Mobility Management Strategy Based on User Mobility Patterns in Wireless Networks” – IEEE transactions on vehicular technology, VOL. 56, NO. 1, JANUARY 2007

John P.Wangermann & Robert F. Stengel, “Principled negotiation between intelligent agents: a model for air traffic management” Artificial Intelligence in Engineering 12 (1198), Elseiver Publication, Page No 177-187.

N. R. Jennings, P. Faratin, A. R. Lomuscio, S. Parsons, C. Sierra, and M. Wooldridge; “Automated Negotiation: Prospects, Methods and Challenges,” International. Journal of group decision and negotiation, 10(2):19-215, 2001

P.Faratin, C.Sierra, and N.R. Jennings (1198) “Negotiation Decision Functions for Autonomous Agents” Int. Journal of Robotics and Autonomous Systems 24 (3-4) 159-82.

S.Kraus and D.Lehman “Designing and building an automated negation agent,” Computational Intelligence, 11(1) 132-171

http://www.iam.ecs.soton.ac.uk/extra/abc/neg.php

A.Sathi and M.s Fox (1989) “Constraint directed negotiation of resource allocation” Distributed Artificial Intelligence II, 163-195, Morgan Kaufmann

A. Oualid Djekoune, Karim Achour and Redouane Toumi “A Sensor Based Navigation Algorithm for a Mobile Robot using the DVFF Approach,” International Journal of Advanced Robotic Systems, Vol. 6, No. 2 (2009) ISSN 1729-8806, pp. 97-108

A. O. Djekoune, K. Achour and R. Toum, “A sensor based navigation algorithm for a mobile robot using the DVFF approach”, International Journal of Advanced Robotic Systems, Vol. 6, pp.97-108, 2009.

S. Koenig and M. Likhachev, “Fast replanning for navigation in unknown terrain,” IEEE Trans. On Robotics, Vol. 21, pp. 354-363, 2005.

A. Poncela, C. Urdiales, E. J. Perez and F. Sandoval, “A new efficiency‐weighted strategy for continuous human/robot cooperation in navigation,” IEEE Transaction .on Systems, Man and Cybernetics Part A: Systems and Humans, Vol. 39, pp. 486-500, 2009.

J. Minguez, L. Montano, “Sensor based robot motion generation in unknown, dynamic and troublesome scenarios,” Robotics and Autonomous Systems, Vol. 52, pp. 290-311, 2005.

Shu-Yun Chung and Han-Pang Huang, “Predictive Navigation by Understanding Human Motion Patterns,” International Journal of Advanced Robotic Systems, Vol. 8, No. 1 (2011) ISSN 1729-8806, pp 52-64

H. Choset, K. M. Lynch, S. Hutchinson, G. Kantor, W. Burgard, L. E. Kavraki and S. Thrun. Principles of Robot Motion: Theory, Algorithms, and Implementations. MIT Press, Boston, 2005.

A* Algorithm Tutorial.

http://www.geocities.com/jheyesjones/astar.html

Patrick Lester. A* Path finding for Beginners.

http://www.policyalmanac.org/games/aStarTutorial.htm

Maxim Likhachev, Geo Gordon and Sebastian Thrun, "ARA*: Anytime A* with Provable Bounds on Sub-Optimality," Advances in Neural Information Processing Systems 16 (NIPS), MIT Press, Cambridge, MA, 2004.

A* Search Algorithm.

http://en.wikipedia.org/wiki/A*_search_algorithm

Andreas Koestler, Thomas Bräunl, “Mobile Robot Simulation with Realistic Error Models”, 2nd International Conference on Autonomous Robots and Agents December 13-15, 2004 Palmerstone North, New Zealand

Leon Zlajpah (2010). “Robot Simulation for Control Design, Robot Manipulators Trends and Development,” Agustin Jimenez and Basil M Al Hadithi (Ed.), ISBN: 978-953-307-073-5, InTech

R.Zlot, A.Stentz, M.B.Dias, and S.Thayer. “Multi-robot exploration controlled by a market economy,” In Proceedings of the 2002 IEEE International Conference on Robotics and Automation, pages 3016–3023, 2002

Ting Zhang*, Shi-Gang Cui, Li Yang and Ji-Gong Li, “Research on Mobile Robot Path Planning Based on D * Algorithm”, 16th International Conference on Mechatronics Technology, October 16-19, 2012, Tianjin, China

Castillo, R.A., Rosario, J.M., Aviles, O.F., Supervision and control architecture proposal for automation and robotics training on platform, (2012) International Review of Mechanical Engineering (IREME), 6 (5), pp. 1025-1034.


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