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Programming Khepera II robot for autonomous navigation and exploration using the hybrid architecture

Authors:

Cen Li,

Bryan Bodkin,

James LancasterAuthors Info & Claims

ACMSE '09: Proceedings of the 47th annual ACM Southeast Conference

Article No.: 31, Pages 1 - 6

https://doi.org/10.1145/1566445.1566488

Published: 19 March 2009 Publication History

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Abstract

This project investigated the feasibility of programming the Khepera II robot for autonomous navigation and exploration using the hybrid robot architecture. At the deliberative layer of the system, the D* Lite algorithm was implemented to find the shortest path between a starting and a destination state, and to perform efficient re-planning during exploration. At the reactive layer, instructions along the shortest path are executed one instruction at a time. Each instruction is executed by following a behavior until a terminator state is reached. Robot exploration is activated when an unexpected world situation is detected along the navigation path. This information is fed to the deliberative layer where the map is updated, and the shortest path was recomputed. A separate visualization module was built to monitor the progress of the navigation and exploration progress. The tool provides a real time feed for the state of robot navigation progress.

References

[1]

Antonelli, G., Arrichiello, F., and Chiaverini, S., "Experiments of Formation Control with Multi-Robot Systems using the Null-Space-Based Behavioral Control", in Proceedings of the 14th Mediterranean Conference on Control and Automation, pp. 1--6, 2006.

Google Scholar

[2]

Antonelli, G., Arrichiello, F., and Chiaverini, S., "An Experimental Study of the Entrapment/Escorting Mission for a Multi-Robot System", IEEE Robotics and Automation Magazine. Special Issues on Design, Control, and Applications of Real-World Multi-Robot Systems, vol. 15, n. 1, pp. 22--29, 2008.

Crossref

Google Scholar

[3]

Challinger, J. "Efficient use of robots in the undergraduate curriculum", in the proceedings of the SIGCSE'05, Feb 23--27^th, 2005, pp. 436--440.

Digital Library

Google Scholar

[4]

Arieo, A. and Gerstner, W., "Hipppocampal spatial model for state space representation in robotic reinforcement learning", in Proceedings of the fifth European Workshop on Reinforcement learning, 2001, p. 1--3, CKI, Utrecht University, 2001.

Google Scholar

[5]

Harlan, R. M, Levine, D. B., and McClarigan, S., "The Khepera robot and the kRobot class: a platform for introducing robotics in the undergraduate curriculum", in the proceedings of the 32^nd SIGCSE technical symposium on computer science education", pp. 105--109. 2001.

Digital Library

Google Scholar

[6]

Harlan, R. M. and McClarigan, S., "Creating emergent behaviors: two robotics labs that combine reactive behaviors", in the proceedings of the 36^th SIGCSE technical symposium on computer science education. Feb. 2005, pp. 441--445.

Digital Library

Google Scholar

[7]

Koenig, S. and Likhachev, M., "Improved fast replanning for robot navigation in unknown terrain", in the proceedings of the IEEE International conference on robotics and automation, pp. 968--975, Washington, DC, May 11--15^th, 2002.

Google Scholar

[8]

Kumar, A. N., "Three years of using robots in an artificial intelligence course: lessons learned", in the Journal on Educational Resources in Computing. 4(3), article 1, pp 1--15.

Digital Library

Google Scholar

[9]

Murphy, R., "Introduction to AI Robotics", first edition, the MIT press, 2000.

Digital Library

Google Scholar

[10]

S. Nolfi, D. Floreano, Evolutionary Robotics, MIT Press, 2000.

Digital Library

Google Scholar

[11]

Russell, S. J., and Norvig, P., "Artificial Intelligence: Modern Approach", second edition, Prentice Hall. 2003.

Digital Library

Google Scholar

[12]

Stentz, A., "Optimal and efficient path planning for partially-known environments", in proceedings of the IEEE International conference on robotics and automation, pp. 3310--3317. 1994.

Crossref

Google Scholar

[13]

Stentz, A. "The focused D* algorithm for real-time replanning". In Proceedings of the International Joint Conference on Artificial Intelligence, pp. 1652--1659, 1995.

Digital Library

Google Scholar

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Sultanova AAbdullayeva M(2021)Path Planning Collision Free for Warehouse Mobile Robot11th World Conference “Intelligent System for Industrial Automation” (WCIS-2020)10.1007/978-3-030-68004-6_25(196-200)Online publication date: 17-Mar-2021
https://doi.org/10.1007/978-3-030-68004-6_25
Sultanova A. B. Abdullayeva M. Y. (2020)PLANNING THE TRAJECTORY OF A WAREHOUSE MOBILE ROBOTInternational Academy Journal Web of Scholar10.31435/rsglobal_wos/30092020/7184Online publication date: 11-Sep-2020
https://doi.org/10.31435/rsglobal_wos/30092020/7184
Qinghua SJuntao L(2017)BP-MPSO Algorithm for PUMA Robot Vacumn Path PlanningProceedings of the International Conference on Advanced Intelligent Systems and Informatics 201710.1007/978-3-319-64861-3_1(3-12)Online publication date: 31-Aug-2017
https://doi.org/10.1007/978-3-319-64861-3_1
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ACMSE '09: Proceedings of the 47th annual ACM Southeast Conference

March 2009

430 pages

ISBN:9781605584218

DOI:10.1145/1566445

Conference Chair:
John D. McGregor

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 19 March 2009

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National Science Foundation

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ACM SE 09

ACM SE 09: ACM Southeast Regional Conference

March 19 - 21, 2009

South Carolina, Clemson

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Sultanova AAbdullayeva M(2021)Path Planning Collision Free for Warehouse Mobile Robot11th World Conference “Intelligent System for Industrial Automation” (WCIS-2020)10.1007/978-3-030-68004-6_25(196-200)Online publication date: 17-Mar-2021
https://doi.org/10.1007/978-3-030-68004-6_25
Sultanova A. B. Abdullayeva M. Y. (2020)PLANNING THE TRAJECTORY OF A WAREHOUSE MOBILE ROBOTInternational Academy Journal Web of Scholar10.31435/rsglobal_wos/30092020/7184Online publication date: 11-Sep-2020
https://doi.org/10.31435/rsglobal_wos/30092020/7184
Qinghua SJuntao L(2017)BP-MPSO Algorithm for PUMA Robot Vacumn Path PlanningProceedings of the International Conference on Advanced Intelligent Systems and Informatics 201710.1007/978-3-319-64861-3_1(3-12)Online publication date: 31-Aug-2017
https://doi.org/10.1007/978-3-319-64861-3_1
Das PSahoo BBehera HVashisht S(2016)An improved particle swarm optimization for multi-robot path planning2016 International Conference on Innovation and Challenges in Cyber Security (ICICCS-INBUSH)10.1109/ICICCS.2016.7542324(97-106)Online publication date: Feb-2016
https://doi.org/10.1109/ICICCS.2016.7542324
Das PBehera HJena PPanigrahi B(2016)Multi-robot path planning in a dynamic environment using improved gravitational search algorithmJournal of Electrical Systems and Information Technology10.1016/j.jesit.2015.12.0033:2(295-313)Online publication date: Sep-2016
https://doi.org/10.1016/j.jesit.2015.12.003
Panda MDas PPradhan SBehera H(2015)An improved gravitational search algorithm and its performance analysis for multi-robot path planning2015 International Conference on Man and Machine Interfacing (MAMI)10.1109/MAMI.2015.7456577(1-8)Online publication date: Dec-2015
https://doi.org/10.1109/MAMI.2015.7456577

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