Switching between formations of multi-robot systems
In this work we aim to introduce the multi agent robotic systems (MARS) to make a good understanding of how it works. In continue, most of the control algorithm like behavior based, leader follower, and virtual structure, artificial potential based control and many more methods have been covered. Th...
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| Main Author: | |
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| Format: | Thesis |
| Language: | English |
| Published: |
2012
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| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/36535/1/MahdiTousizadehSedehiMFKE2012.pdf |
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| Summary: | In this work we aim to introduce the multi agent robotic systems (MARS) to make a good understanding of how it works. In continue, most of the control algorithm like behavior based, leader follower, and virtual structure, artificial potential based control and many more methods have been covered. The control procedure of multi agent robotic is generally divided into two basic parts. First is the path trajectory and the second part is switching between the formations. Summation of these two commands will be injected to the robots actuators. In the third chapter the two main methods, Behavior-Based and Leader-Follower method is surveyed in detail to investigate the parameters that can affect the formation of the group. Basically, in the behavior based control algorithm each robot acts regardless of the group decision, which is not suitable for our goal, so we focus on the other methodleader follower- to catch the result. A method for switching strategy is mentioned at the end of chapter three that is combination of leader follower strategy with matrix based control algorithm to make the better switching controller when the group of robot is facing with the an obstacle. The controller deals with the information coming from the sensorial reading. In the case that the group is facing with an external object, the controller checks the feasibility of the formation patterns to choose one of them as the new formation. Mean Task Allocation is used in utilization function to represents the new formations of robots location in matrix form. In continue, there is a cost function to optimize the selection of new formation. The proposed algorithm has been verified using MATLAB Simulation and the results are satisfactory. |
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