基于遗传算法和B 样条曲线的平滑避障路径规划

传统的避障路径规划中常常存在不连续点,提出一种新的平滑避障路径规划的方法—遗传算法和B样条曲线法。首先,先通过碰撞侦测,能够侦测出前进路径中的障碍物,然后通过遗传算法再结合B样条曲线规划出平滑的避障路径。该算法可以避免运动过程因打滑而造成与目标位置的误差,解决机器人在静态环境中全局、局部路径规划和规划路径中存在不连续点的问题。仿真和实验结果证明了算法的有效性。

Smoothing Obstacle Avoidance Path Planning Based on Genetic Algorithms and B-spline Curve

Traditional path planning and obstacle avoidance of discontinuities often exist. This paper presents a new obstacle avoidance path planning for a smooth approach-genetic algorithms and B-spline curve. First of all, first through the collision detection, can detect obstacles in the path ahead, then the genetic algorithm combined with B-spline curve and then map out a smooth obstacle avoidance path. The algorithm can avoid skidding caused by movement and target location error, solve the robot in a static environment, global, local path planning and path planning problem of discontinuity exists. Simulation and experimental results show the effectiveness of the algorithm.