Abstract
This paper presents a new approach for solving one of the crucial robotic tasks: the global path planning problem. It consists in calculating the existing optimal path, for a non-point, non-holonomic robot, from start to goal position in terms of Non Uniform Rational B-Spline (NURBS) curve. With a priori knowledge of the environment and the robot characteristics (size and radius of curvature), the algorithm begins by selecting a set of control points derived from the shortest, collision-free polyline path. Then, an optimized NURBS curve modelling using Genetic Algorithm (GA) is introduced to replace that polyline path by a smooth curvature-constrained curve which avoids obstacles. Computer simulation studies demonstrate the effectiveness of the proposed method.
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Jalel, S., Marthon, P., Hamouda, A. (2015). Optimized NURBS Curves Modelling Using Genetic Algorithm for Mobile Robot Navigation. In: Azzopardi, G., Petkov, N. (eds) Computer Analysis of Images and Patterns. CAIP 2015. Lecture Notes in Computer Science(), vol 9256. Springer, Cham. https://doi.org/10.1007/978-3-319-23192-1_45
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DOI: https://doi.org/10.1007/978-3-319-23192-1_45
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