基于激光扫描区域动态变化的智能叉车障碍物检测

Intelligent forklift obstacle detection based on dynamic change of laser scanning area

为了解决干果仓储过程中智能叉车行驶过程的障碍物误检问题,该文提出一种基于车速与转向角的智能叉车障碍物动态检测方法。智能叉车通过车载激光传感器实时获取车身位姿和周围环境信息,并结合所建立的叉车运动几何模型,形成基于水平和倾斜激光测距传感器扫描面的双面融合障碍物动态检测方式,使得智能叉车的障碍物检测区域随车速及转向角动态变化。试验结果表明:水平扫描测距传感器的试验中,该文方法未出现误检情况,而扇形方法误检率为50.00%,矩形方法误检率为10.00%;倾斜扫描测距传感器的试验中,该文方法未出现误检情况,而扇形方法误检率为30.77%,矩形方法误检率为69.23%。该文方法的警情预测与实际相符,以水平扫描测距传感器为主,倾斜扫描测距传感器为辅,能够检测到的障碍物最低高度约为31mm,有效解决了智能叉车在仓库中的障碍物误检问题,较传统障碍物检测方法更适用于仓储运输,提高了智能叉车在仓库中的机动性和安全性。该研究可为体型较大的仓储智能运输车辆的障碍物检测方法提供参考。

Dried fruits should be stored in warehouse by placing and stacking on the shelves.By using intelligent forklift to store and take goods on the shelves,the warehouse efficiency could be effectively solved,and the warehouse management of dried fruits could be promoted to be standardized and intelligent.Obstacle detection is the primary guarantee for the safe operation of intelligent forklifts,and the detection effect is also related to the efficient operation of intelligent forklifts in warehouse,as a key technology of intelligent vehicles,it has gradually become a research hot topic.However,the current researches focuse on small multi-degree-freedom intelligent vehicles,there is no research on obstacles detection methods for large intelligent forklift in dried fruit warehouse.Considering the limitations of warehouse layout,the detection region of traditional detection methods were mostly fixed shape,that means that the safety distance was fixed,so it was more suitable when forklift going straight in an open space,on the contrary,in the dried fruit warehouse with limited channel width,especially when turning,there would be false alarm,which would easily cause the large intelligent forklift to misjudge the objects that could be bypassed into potential obstacles,thus causing the forklift to change the road or stop sharply.In order to solve the false detection and realize the obstacle dynamic detection for large intelligent forklift in dried fruit warehouse,taking the reversing process of intelligent forklift as an example,an obstacles dynamic detection method based on dynamic change of laser scanning area with the speed and steering angle of large intelligent forklift in dried fruit warehouse was proposed in this paper.The real-time position and direction information of forklift in the global Cartesian coordinate system of warehouse was obtained by using on-board laser sensor SICK-NAV350,combining with the motion geometry model of forklift,the horizontal laser ranging sensor(SICK-LMS111)and the inclined laser ranging sensor(SICK-TIM561)scanning the obstacle in 2 planes,forming a dynamic detection area changing with the speed and steering angle of forklift.The real vehicle test results showed that the proposed method without error checking,the error detection rate of the sector method was 50.00%and that of the rectangle method was 10.00%in the testing of horizontal scan ranging sensor,the error detection rate of the sector method was 30.77%and that of the rectangle method was 69.23%in the testing of tilted scan ranging sensor.With tilted scanning range sensor as the auxiliary and horizontal scanning range sensor as the main part,a dynamic obstacle detection area based on fusion of 2 planes was formed,the minimum height of obstacles could be detected was about 31 mm when the installation angle of sensor SICKTIM561 was 25.60°,the height to ground was 2 000 mm and the detection region width was set to 2 183 mm.The proposed method effectively solved the false alarm of intelligent forklift when driving in the warehouse,and was more suitable for warehousing and transportation than the traditional detection method,and improved the mobility and safety of intelligent forklift in warehouse.The research can provide reference for obstacle detection of large warehouse intelligent transport vehicles.