摘要
Abstract
When solving the robot following and formation decision-making model,due to the complex shape of the for-mation,the decision-making strategy cannot guarantee the consistency between the following route and the preset route,resulting in low tracking accuracy of the formation.Therefore,a high-density storage robot following and formation technology based on time grid method and immune algorithm is proposed.Using the grid method to convert the two-dimen-sional workspace of the storage robot into a grid map,and introducing a time dimension to calculate the grid values of each grid,the position of obstacles is calibrated based on the grid values and environmental measurement information,and the feasible area of the robot is determined.Combining the kinematic model of the navigation robot and the linear function of the error amount,the wheel odometer is used to estimate the motion speed of the navigation robot.Based on this,the objective function is to minimize the following error and the stability of the automated formation.A robot following formation model is established by integrating constraints such as the following error and formation shape,and an immune algorithm is used to solve the model to obtain the robot following formation strategy.The experimental results show that using the proposed method for following formation decision-making of warehousing robots,the yaw angle of the following robots is kept below 0.2 °,with good following consistency and high following formation accuracy.关键词
时间栅格法/高密度仓储机器人/跟随编队/免疫算法/动态环境Key words
time grid method/high density warehousing robots/following formation/immune algorithm/dynamic environment分类
信息技术与安全科学
