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NURBS Based Multi-objective Path Planning

机译:基于NURBS的多目标路径规划

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Path planning presents a key question for an autonomous robot to evolve in its environment. Hence, it has been largely dealt in recent years. Actually, finding feasible paths and optimizing them for different objectives is computationally difficult. In this context, this paper introduces a new mobile robot path planning algorithm by introducing an optimized NURBS (Non Uniform Rational B-Spline) curve modelling using Genetic Algorithm to represent the generated path from the specified start location to the desired goal. Thus, given an a priori knowledge of the environment, an accurate fitness function is used to compute a curvature-constrained and obstacles-avoiding smooth path, with minimum length and low variations of curvature. The performance of the proposed algorithm is demonstrated through extensive MATLAB simulation studies.
机译:路径规划为自主机器人在其环境中发展提出了一个关键问题。因此,近年来已在很大程度上解决了这一问题。实际上,找到可行的路径并针对不同的目标对其进行优化在计算上很困难。在这种情况下,本文介绍了一种新的移动机器人路径规划算法,方法是使用遗传算法引入优化的NURBS(非均匀有理B样条曲线)曲线建模,以表示从指定起始位置到所需目标的生成路径。因此,在事先了解环境的情况下,可以使用精确的适应度函数来计算曲率受限且避开障碍物的平滑路径,且长度最小且曲率变化较小。通过广泛的MATLAB仿真研究证明了该算法的性能。

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