摘要
仓储物流环境中的搬运机器人数量较多,路径的可选择性较高,其智能导航是确保高效物流的关键因素。提出物流搬运智能机器人信息融合导航方法。引入秩卡曼滤波算法,预测出机器人运动状态。基于秩采样原理,得出机器人运动采样点集,计算机器人运动状态的估计值以及误差协方差矩阵的预测值。选用Grubbs判定法排除机器人运动状态测量值中的无效数据,将所有传感器数据归一化处理,获取数据权重,完成机器人导航数据的融合。根据融合数据规划出物流搬运智能机器人的导航路线,同时控制机器人的角速度和线速度,实现物流搬运智能机器人导航。实验结果表明,所提方法的避障效果较好,机器人的线速度和角速度的控制结果与理想数据一致,与文献方法相比,导航路径更短。
There are many handling robots with high path selectivity in the storage and logistics environment.And their navigation is the key factor to ensure efficient logistics.In this paper,a navigation method of information fusion for logistics handling smart robots was proposed.Firstly,an augmented Kalman filtering algorithm was introduced to predict the motion state of the robot.Based on the rank sampling principle,the set of motion sampling points was obtained.Secondly,the estimated value of the motion state and the predicted value of the error covariance matrix were calculated simultaneously.Moreover,the Grubbs decision method was selected to eliminate the invalid data in the measured value of the robot motion state,and then all sensor data were normalized to obtain data weight,and thus to complete the data fusion of robot navigation.According to the fusion data,the navigation route was planned.Meanwhile,the angular velocity and linear velocity of the robot were controlled.Finally,the navigation of the logistics handling smart robot was achieved.Experimental results show that the avoiding effect of the proposed method is better than that of the literature method.And the control results of the linear speed and angular speed are consistent with the ideal data,and the navigation path is shorter.
作者
漆圆方
郭明德
QI Yuan-fang;GUO Ming-de(Jiangxi University of Applied Science,Nanchang Jiangxi 330100,China;Xinjiang Agricultural University,Urumqi Xinjiang 830052,China)
出处
《计算机仿真》
北大核心
2023年第10期426-430,共5页
Computer Simulation
基金
2021年中国物流学会《能力本位视觉下应用型本科课程设计的研究与实践》《现代仓储管理实务》(JZW2021122)。
关键词
物流搬运
智能机器人
信息融合
导航
机器人控制
Logistics handling
Smart robot
Information fusion
Navigation
Robot control
