农业机械学报2018，Vol.49Issue(4)：36-44,9.DOI:10.6041/j.issn.1000-1298.2018.04.004
拖拉机自动驾驶系统上线轨迹规划方法
Guided Trajectory Planning Method for Tractor Autopilot System
摘要
Abstract
The existing tractor autopilot system relies on the built-in path tracking algorithm to approach a target point on the global path when the driver starts the navigation mode at any position in the field.The tracking path will produce a shock phenomenon near the target point,it will affect the path tracking accuracy,and the entire approach process is uncontrollable.In order to solve this problem,a guided trajectory planning method based on third-order B-spline theory was proposed.The trajectory with the minimum length was taken as the desired path,the maximum curvature constraint,the maximum steering angle constraint and the heading of starting goal point constraint were taken into account.Quantum genetic algorithm (QGA) was used to optimize the control points,and finally the B-spline theory was used to generate a smooth desired trajectory.Four kinds of operating conditions were tested in Matlab environment.The simulation results showed that the B-spline theory based on the QGA could be used to obtain a trajectory satisfying the multiple nonlinear constraints,and the trajectory curvature change was continuous,which was beneficial to the path tracking controller.A field test was carried out,and the results showed that the pure pursuit algorithm alone had a travel distance of 78.6 m,and the travel distance based on the guided trajectory planning method was 23.7 m.Compared with the existing autopilot system,the trajectory planning method based on B-spline theory was helpful to control the shape of tracking path and improve the controllability of approach process.关键词
拖拉机/自动驾驶系统/量子遗传算法/B样条理论/轨迹规划Key words
tractor/autopilot system/quantum genetic algorithm/B-spline theory/trajectory planning分类
农业科技引用本文复制引用
贾全,张小超,苑严伟,赵博,伟利国,付拓..拖拉机自动驾驶系统上线轨迹规划方法[J].农业机械学报,2018,49(4):36-44,9.基金项目
国家重点研发计划项目(2017YFD0700400、2017YFD0700403)和湖南省战略性新兴产业科技攻关类项目(S2016GXZLGG0101) （2017YFD0700400、2017YFD0700403）
