Name
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, collisionfree 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. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1007/978-3-319-23192-1_45 | COMPUTER ANALYSIS OF IMAGES AND PATTERNS, CAIP 2015, PT I |
Keywords | Field | DocType |
NURBS curves parameterization, Robot path planning, Path smoothing, Curvature constraint, Genetic algorithm | Motion planning,Computer vision,Computer science,Radius of curvature,Robot path planning,A priori and a posteriori,Artificial intelligence,Mobile robot navigation,Robot,Genetic algorithm | Conference |
Volume | ISSN | Citations |
9256 | 0302-9743 | 1 |
PageRank | References | Authors |
0.36 | 11 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sawssen Jalel | 1 | 2 | 1.43 |
| Philippe Marthon | 2 | 1 | 0.36 |
| Atef Hamouda | 3 | 40 | 12.57 |