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Thesis (Doctor of Philosophy) >
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http://hdl.handle.net/2080/670
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| DC Field | Value | Language |
|---|
| contributor.author | Pradhan, Saroj Kumar | - |
| contributor.author | Parhi, D K (Guide) | - |
| contributor.author | Panda, A K | - |
| date.accessioned | 2008-04-24T09:10:12Z | - |
| date.available | 2008-04-24T09:10:12Z | - |
| date.issued | 2007 | - |
| identifier.citation | Navigation Techniques for Control of Multiple Mobile Robots, Thesis Submitted in partial fulfillment of the requirements for the award of Doctor of Philosophy in Engineering to National Institute of Technology, Rourkela | en |
| identifier.uri | http://hdl.handle.net/2080/670 | - |
| description | Copyright for the thesis belongs to National Institute of Technology Rourkela | en |
| description.abstract | The investigation reported in this thesis attempt to develop efficient techniques for the control of multiple mobile robots in an unknown environment. Mobile robots are key components in industrial automation, service provision, and unmanned space exploration. This thesis addresses eight different techniques for the navigation of multiple mobile robots. These are fuzzy logic, neural network, neuro-fuzzy, rule-base, rule-based-neuro-fuzzy, potential field, potential-field-neuro-fuzzy, and simulated-annealing- potential-field- neuro-fuzzy techniques.
The main components of this thesis comprises of eight chapters. Following the literature survey in Chapter-2, Chapter-3 describes how to calculate the heading angle for the mobile robots in terms of left wheel velocity and right wheel velocity of the robot.
In Chapter-4 a fuzzy logic technique has been analysed. The fuzzy logic technique uses different membership functions for navigation of the multiple mobile robots, which can perform obstacles avoidance and target seeking.
Chapter-5 consists of two subsections. In first subsection the neural network technique has been developed and analysed for controlling the multiple mobile robots. Then this technique is hybridised with fuzzy logic to improve the fuzzy logic controller of Chapter-4 with the addition of a neural network as a pre-processor for the fuzzy controller.
Chapter-6 analyses a rule-based-neuro-fuzzy technique for controlling the mobile robots. A rule-base technique is first developed and then it is combined with the neuro-fuzzy technique of Chapter-5 to increase its efficiency.
Chapter-7 deals with an efficient potential field method for navigation of multiple mobile robots. Then a hybrid potential-field-neuro-fuzzy technique for controlling the mobile robots is described.
Finally, Chapter-8 analyses the optimisation of potential field with the help of simulated annealing for escaping local minima. The developed potential-field-simulated-annealing-neuro-fuzzy technique is described in simulation as well as for real mobile robots. | en |
| format.extent | 8202260 bytes | - |
| format.mimetype | application/pdf | - |
| language.iso | en | - |
| publisher | National Institute of Technology, Rourkela | en |
| title | Navigation Techniques for Control of Multiple Mobile Robots | en |
| type | Thesis | en |
| Appears in Collections: | Thesis (Doctor of Philosophy)
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Files in This Item:
| File |
Description |
Size | Format |
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| Errata of the Thesis.pdf | | 173Kb | Adobe PDF | View/Open | | thesis-Pradhan.pdf | | 7975Kb | Adobe PDF | View/Open |
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