Research On AGV Positioning Technology And Path Planning Method Under Multi-Sensor

With the development of technology,Automatic Guided Vehicles(AGV)have been widely used in various fields.Navigation technology is one of the key technologies to ensure that the AGV reaches the target quickly,safely and accurately.In the indoor environment,the navigation performance of the AGV is affected by its position accuracy and the reasonableness of the driving path.Improving the reliability and work efficiency of the AGV is the core issue of the current research on the AGV.For this reason,this article optimizes from two problems of positioning and path planning.Firstly,To further improve UWB real-time positioning accuracy and reduce coordinate calculation time,this paper proposed an improved precise positioning algorithm.This method divided the positioning process into two phases: the establishment of ranging model and the calculation of positioning coordinates.This paper introduced Sage-Husa adaptive filtering and BP neural network when building the model.Experimental results show that this method can effectively reduce model errors,suppress divergence and improve accuracy.This paper adopted SEF method on the basis of establishing the model,which effectively reduces the error caused by the environment and its own hardware.When solving the positioning coordinates,this paper proposed a new type of positioning calculation method to solve the problem of the time-consuming time of the adaptive intelligent trilateral algorithm.It effectively reduces the speed of coordinate calculation when there is no solution.In order to verify the effectiveness of the positioning algorithm,the static and dynamic state positioning are used for simulation verification.The simulation results show that the positioning algorithm not only improves the positioning accuracy,but also significantly improves the calculation speed,which can be used as an effective positioning method in the actual environment.Secondly,in order to improve the reliability of the positioning system,the Federal Kalman filter algorithm is used to locate UWB and ins.In the indoor environment,the coordinate of AGV is solved by the quaternion method.In order to verify the effectiveness of the fusion algorithm,the algorithm is simulated and verified.Comparing the distribution of location errors before and after fusion,it can be seen that the method can reduce the influence of INS cumulative error on the positioning accuracy,which indicates that the method can effectively integrate the location and improve the precision of positioning.Finally,for the path planning,the path of optimization algorithm planning has the problem of non shortest path.Firstly,matrix the environment,and then the shortest path is judged according to the matrix value of the path.Finally,the non shortest path is optimized according to the designed path optimization algorithm.In order to verify the performance of the algorithm,two path planning algorithms are used to verify the performance of the algorithm.The simulation results show that the method can effectively shorten the path length and improve the efficiency of AGV.