Planning a Mobile Robot in Static and Dynamic Environments

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Chapter.1 Introduction

1.1 Introduction:-
In this Research develops and implements a Genetic Algorithm based approach with a Grid search method for path planning for a mobile robot in Static and dynamic environments. The approach uses the search of the static and dynamic obstacles as search space. Using the Grid search method, it searches an initial feasible path for the robot in the environment. In an environment with obstacles, a mobile robot must be able to generate collision free paths to move from an initial location to a final location, and in order to truly show a level of intelligence these paths must be optimized under some criteria that is most important to the robot, the terrain and the problem given. The approach applies the Genetic algorithm to find the optimal path for the robot.
Mobile robot path planning is a research area of Artificial intelligence and Robotics. Researcher from all over the world have carried out a of studies on robot path planning by using the artificial neural Network , Neuro fuzzy Method, potential field method, ant colony algorithm, genetic algorithm and so on. Artificial potential field method is suitable for underlying real-time path control with the lack of global information. But it has the problem of local path planning. Neural network method has good ability optimization of problem. But in the network structure becomes large when considering lots of obstacles or dynamic
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