Abstract
a new hybrid approach based on a modified Genetic Algorithm (GA) and a modified search algorithm (A*) is proposed to enhance the searching ability of mobile robot movement towards optimal solution state in static environment, and to achieve a multi objectives optimization problem of path and trajectory generating. According to that the cubic spline data interpolation and the non-holonomic constrains in Kinematic equations for mobile robot are used. The objective function of the proposed approach is to minimize traveling distance, and traveling time, to increase smoothness, security, and to avoid collision with any obstacle in the robot workspace. The simulation results show that the proposed approach is able to achieve multi objective optimization efficiently in a complex static environment. Also, it has the ability to find a solution when the number of obstacles is increasing. The mobile robot successfully travels from the starting position to the desired goal with an optimal trajectory as a result of the approach presented in this paper.
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Oleiwi, B.K., Roth, H., Kazem, B.I. (2014). Multi Objective Optimization of Path and Trajectory Planning for Non-holonomic Mobile Robot Using Enhanced Genetic Algorithm. In: Golovko, V., Imada, A. (eds) Neural Networks and Artificial Intelligence. ICNNAI 2014. Communications in Computer and Information Science, vol 440. Springer, Cham. https://doi.org/10.1007/978-3-319-08201-1_6
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DOI: https://doi.org/10.1007/978-3-319-08201-1_6
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