Research on Target Location Model of Mine Mobile Robot Based on Multi-vision Sensor
The operating environment of mine is complicated and dangerous,which greatly reduces the positioning accu-racy of underground mobile robot,therefore,the target location model of mine mobile robot based on multiple vision sensors is proposed.Firstly,a sensor system containing multiple cameras and depth sensors is designed to obtain rich environmental infor-mation.These sensors,by working in conjunction with mobile robots,can provide accurate three-dimensional scene perception.Secondly,an object detection and recognition algorithm based on deep learning is proposed.By training a regional deep convo-lutional neural network,it can accurately detect and identify downhole target objects,such as equipment and personnel,from the image data obtained by the sensor.Finally,a fusion positioning algorithm is developed,which combines the visual information obtained by the sensor with the robot's motion model to realize the accurate positioning of the mobile robot in the coal mine.The algorithm can update the position and attitude of the robot in real time according to the sensor data and the motion informa-tion of the robot,so as to achieve the goal of accurate positioning.The validity and robustness of the proposed positioning model are verified by experiments in actual mine environment.The experimental results show that the model can accurately locate the target object in the complex and dangerous coal mine environment,and provide reliable support for the safe and efficient opera-tion of the underground mobile robot.
mine mobile robotmulti-vision sensortarget positioningfusion positioning
万方数据
维普
