基于动态识别区和B样条曲线的智能叉车避障路径规划

Obstacle Avoidance Path Planning for Intelligent Forklift Truck Based on Dynamic Identification Zone and B-spline Curve

为降低干果仓储智能叉车自主避障误警率,提高仓储空间有效利用率,结合叉车运行环境特点,基于激光传感器,设立探测范围随车速、等效转向角变化的动态识别区,有效探测叉车行进方向上的障碍物;将获得的障碍物特征控制点作为分割点,采用四次五阶准均匀B样条曲线,分前后段合并生成满足叉车最小转弯半径、曲率连续、最大转向轮角速度等多约束条件下的避障路径;对仓库中的直行路段和转弯路段进行避障路径规划试验,结果表明所得避障路径满足各项约束,曲率不大于1. 06×10-3mm-1,等效转向角不大于60°,等效转向轮角速度不大于1. 05 rad/s,验证了算法的可行性。

In order to reduce the false alarm rate of autonomous obstacle avoidance for intelligent forklift trucks in dried fruit warehouse and improve the utilization rate of warehouse space, combining with the characteristics of the operating environment of forklift truck, and basing on the laser sensor SICK LMS111 and SICK NAV350, a dynamic identification zone that the detection range was changed along with the speed and equivalent steering angle was set up to effectively detect obstacles in the direction of travel. Then, feature control point obtained by obstacles was taken as the segmentation point, and the quartic five-order quasi-uniform B-spline curves were used to generate the obstacle avoidance path by combining front and rear segments of curve, which met the multi-constraint conditions such as the minimum turning radius, the continuous curvature and the maximum angular velocity of steering wheel. By carrying out the obstacle avoidance path planning tests on the straight road section and the turning in the warehouse, the results showed that the obstacle avoidance paths satisfied various constraints, the curvature was not more than 1.06×10^-3 mm^-1 , equivalent steering angle was not more than 60°, angular velocity of equivalent steering wheel was not greater than 1.05 rad/s, which effectively verified the feasibility of the algorithm. It can be used as a reference for obstacle avoidance technology of similar large warehouse intelligent vehicles.