Speed Measurement And Positioning Algorithm Based On Single Line Lidar

At present,with the development of IOT and artificial intelligence,research on indoor positioning and mapping has received more attention.Human beings spend more and more time indoors,and various indoor positioning services have emerged.In the fields of personal services,catering logistics,medical improvement,scientific research,etc.,indoor positioning and mapping can be more effective and play an important role.Existing indoor positioning solutions are difficult to achieve accuracy below the centimeter level,and they need to rely on multiple devices,which not only increase the cost,but also increase the difficulty of actual operation.Combining the characteristics of lidar data,this paper proposes a new car speed measurement and positioning scheme,which will bring some new ideas to indoor positioning.The key to accurate indoor positioning of a mobile car is to obtain an accurate pose estimation.The more accurate the pose estimation is,the more accurate the positioning of the mobile car will be,so as to establish a more reliable map and lay a good foundation for subsequent path planning.At present,most indoor positioning algorithms are difficult to achieve real-time and accurate positioning.Although some SLAM algorithms using single-line lidar can achieve positioning,most of them are based on inter-frame matching,and there are still certain errors.It is difficult to control the accuracy at the centimeter level.In this article,based on the characteristics of the point cloud data change when the single-line lidar sweeps to one side of the obstacle,the movement state information of the robot car is analyzed mathematically.In addition,this article also established a motion model based on the characteristics of the car's motion to provide point cloud data with higher accuracy.We solved a series of problems when we used the solution in this article for positioning.First,because the data accuracy of the existing single-line lidar equipment is not high,and the movement state of the robot car is difficult to control,which is not conducive to theoretical analysis,this paper establishes an indoor sports scene model to compare the data of the robot car with single-line lidar.The movement is modeled to construct error-free ideal data and noisy data,and analyze and calculate on this basis.Second,because the car is always in motion,if the frame matching is performed according to the traditional idea,there is only one positioning in a frame,then positioning errors will always occur.Based on the characteristics of the robot car in different motion states,this paper proposes a point-by-point analysis of mileage calculation method,which can accurately solve the motion state information of the robot car.In theory,it can achieve no positioning error.Third,it is necessary to know the movement state of the robot car in advance in order to perform specific calculations.This paper proposes a new method to judge the real-time movement state of the robot car.Fourth,when using point cloud data,it is also necessary to determine which wall the point cloud is generated from.This article proposes a new method to distinguish the point cloud data scanned on different walls.Different from other indoor positioning systems,this article is mainly based on the data characteristics of single-line lidar to mathematically calculate some of its own state at the current moment,and then can achieve high-precision indoor positioning.However,this method relies on high-precision single-line laser radar.The lidar equipment on the market cannot meet the demand for the time being.Therefore,this article obtains experimental data by modeling the movement of the car and Lidar,and simulates the real situation by adding noise to the ideal data.At present,with the development of the Internet and artificial intelligence,indoor positioning has received more attention.80% of the human life is spent indoors,and a large number of positioning needs of individual users,service robots,new Internet of Things devices,etc.also occur indoors.Therefore,the accurate positioning of robots in indoor scenes has Indoor services are very important.Existing indoor positioning solutions,the accuracy is difficult to reach below the centimeter level,and it needs to rely on multiple devices,which not only increases the cost,but also increases the difficulty of the actual operation.In this article,this article combines the characteristics of lidar data and proposes a new indoor vehicle speed measurement and positioning scheme will bring some new ideas to indoor positioning.