Final thesis detail
||Expert Systems and Advanced Algorithms in Mobile Robots Path Planning
||Ahmad Abbadi, Ph.D.
||doc. Ing. Radomil Matoušek, Ph.D.
||The opponent will be displayed after his opinion is published.
||Faculty of Mechanical Engineering
||Design and Process Engineering
||Defended (thesis was successfully defended)
Characteristics of thesis dilemmas:|
The aims of the thesis are to improve the mobile robot strategy for global path planning, by proposing new approaches to improve the completeness and efficiency of planning algorithms, which in consequence improve the robot’s autonomy. Then assert the results statistically, and compare it to other methods.
Objectives which should be achieve:|
• Review of the state of the art.
• Design new or improve existing approaches for path planning algorithm based on RRT and cell decomposition principles.
• Use knowledge base and fuzzy expert system in the path planning methods.
• Design simulation environment that conducts simulations of the experiments, and evaluates the results statistically.
Motion Planning, Path planning, Rapidly exploring random tree, RRT, Expert system, Fuzzy system, Cell decomposition
Motion planning is an active field in robotics domain, it is responsible for translating high-level specifications of a motion task into low-level sequences of motion commands, which respect the robot and the environments constraints.
In this work many path-planning approaches have been reviewed, mainly, the rapidly exploring random tree algorithm (RRT), the cell decomposition approaches (CD), and the application of fuzzy expert system (FES) in motion planning. These approaches have been adapted to solve some of mobile robots motion-planning problems efficiently, i.e. motion planning in small and narrow areas, the global path planning in dynamic workspace, and the improvement of planning efficiency using available information about the working environments.
New planning approaches have been introduced based on exploiting and combining the advantages of cell-decomposition, and RRT, in addition to use other tools i.e. fuzzy expert system, to increase the efficiency and completeness of finding a solution.
This thesis also proposed solutions for other motion-planning problems, for example the identification of narrow area and the important regions when using sampling-based algorithms, the path shortening for RRT, and the problem of planning a safe path.
All proposed methods were implemented and simulated in Matlab to compare them with other methods, in different workspaces and under different conditions. Moreover, the results are evaluated by statistical methods using Matlab and Minitab environments.
LAVALLE, Steven Michael (2006): Planning algorithms. Cambridge ; New York : Cambridge University Press. ISBN 0-521-86205-1
SLEUMER, Nora and TSCHICHOLD-Gürmann, Nadine (1999): Exact cell decomposition of arrangements used for path planning in robotics. Swiss Federal Institute of Technology, Institute of Theoretical Computer Science http://dx.doi.org/10.3929/ethz-a-006653440
Reason for concealment:|
Tip: a short reference to the final thesis is also: https://www.vutbr.cz/en/studies/final-thesis?zp_id=89369
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