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Mobile Robots Navigation Modeling in Known 2d Environment Based on Petri Nets


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Abstract

The paper deals with supervised robot navigation in known environments. The navigation task is divided into two parts, where one part of the navigation is done by the supervisor system i.e. the system sets the vector marks on the salient edges of the virtual environment map and guides the robot to reach these marks. Mobile robots have to perform a specific task according to the given paths and solve the local obstacles avoidance individually. The salient point’s detection, vector mark estimation and optimal path calculation are done on the supervisor computer using colored Petri nets. The proposed approach was extended to simulate a flexible manufacturing system consisting of swarm of 17 robots, 17 - warehouses and 17 - manufacturing places. Our experimental investigation showed that simulated mobile robots with proposed supervision system were efficiently moving on the planned path.


Keywords


Pages

Total Pages: 8
Pages: 241-248

DOI
10.1080/10798587.2016.1264695


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Published

Volume: 24
Issue: 2
Year: 2018

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References

Borenstein J. Invited paper for the Journal of Robotic Systems, Special Issue on Mobile Robots.

Burguera, Antoni, Yolanda González, and Gabriel Oliver. "Sonar Sensor Models and Their Application to Mobile Robot Localization." Sensors 9.12 (2009): 10217-10243. Crossref. Web. https://doi.org/10.3390/s91210217

Defoort, Michael et al. "Motion Planning for Cooperative Unicycle-Type Mobile Robots with Limited Sensing Ranges: A Distributed Receding Horizon Approach." Robotics and Autonomous Systems 57.11 (2009): 1094-1106. Crossref. Web. https://doi.org/10.1016/j.robot.2009.07.004

Baghaei, Khashayar R., and Arvin Agah. "Task Allocation and Communication Methodologies for Multi-Robot Systems." Intelligent Automation & Soft Computing 9.4 (2003): 217-226. Crossref. Web. https://doi.org/10.1080/10798587.2000.10642855

Al-Jarrah, Omar M., and Yahya M. Tashtoush. "Mobile Robot Navigation Using Fuzzy Logic." Intelligent Automation & Soft Computing 13.2 (2007): 211-228. Crossref. Web. https://doi.org/10.1080/10798587.2007.10642960

Satish, P. & Madhava, K. (2007). Multi robotic conflict resolution by cooperative velocity and direction control. In Sascha Kolski (Ed.), Mobile Robots: Perception & Navigation . ISBN: 3-86611-283-1, InTech Available from: http://www.intechopen.com/books/mobile_robots_perception_navigation/multi_robotic_conflict_resolution_by_cooperative_velocity_and_direction_control.

Sooyong L. International Journal of Control, Automation, and Systems 3.1 (2005)

Shi, Weiren, Kai Wang, and Simon X. Yang. "A Fuzzy-Neural Network Approach To Multisensor Integration For Obstacle Avoidance Of A Mobile Robot." Intelligent Automation & Soft Computing 15.2 (2009): 289-301. Crossref. Web. https://doi.org/10.1080/10798587.2009.10643032

Zhu, Yi et al. "A New Bug‐type Navigation Algorithm for Mobile Robots in Unknown Environments Containing Moving Obstacles." Industrial Robot: An International Journal 39.1 (2012): 27-39. Crossref. Web. https://doi.org/10.1108/01439911211192475

Zhu, Yi et al. "A New Hybrid Navigation Algorithm for Mobile Robots in Environments with Incomplete Knowledge." Knowledge-Based Systems 27 (2012): 302-313. Crossref. Web. https://doi.org/10.1016/j.knosys.2011.11.009

JOURNAL INFORMATION


ISSN PRINT: 1079-8587
ISSN ONLINE: 2326-005X
DOI PREFIX: 10.31209
10.1080/10798587 with T&F
IMPACT FACTOR: 0.652 (2017/2018)
Journal: 1995-Present




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