Research On Obstacle Avoidance Of Indoor UAV Navigation Based On Data Fusion

With the accelerated integration of UAVs and practical applications,UAVs are required to develop in a variety of ways such as intelligence,autonomy and practicality,Among them,intelligentization is a hot spot in the field of UAV research.In general,the key technologies involved in the intelligentization of UAV are: UAV body structure,system structure,multi-sensor system and information fusion,interactive technology,navigation and location,path planning,path tracking,motion control and so on.This paper focuses on the three aspects of indoor unmanned aerial vehicles: multi-sensor data fusion,navigation and positioning,path tracking,to realize the true sense of indoor UAV navigation.Firstly,this paper introduces and elaborates the research background,significance,development status and future development trend of indoor UAV navigation and obstacle avoidance.Secondly,this paper researches on multi-sensor data fusion technology and presents a decision-making idea of using different filters based on different motion states by analyzing the working process?design pattern and decision principle of each filter,taking into account the influence the indoor UAV movement state to its filter accuracy.This not only reduces the filtering error when the indoor UAVs do non-linear motion,but also improves the positioning efficiency when doing linear motion.Thirdly,according to the particularity of indoor unmanned aerial vehicles,this paper makes a deep analysis of the use and application scope of the sensor,and selects inertial navigation,laser range finder,motion detection and other sensors to constitute an indoor UAV integrated navigation system;although the laser range finder is only used for environmental detection,In this paper,it will be used to calculate the absolute position of UAVs.And a loose combination based on the inertial navigation-laser range finder-motion detection sensor is put forward innovatively.In this paper,the sensors are studied from the aspect of data processing,and the principle of position calculation based on laser range finder is described in detail and the corresponding derivation step is given.Then,combining the other existing models,the mathematical model of the loose integrated navigation system is established.According to the characteristics of the model,the Kalman filter algorithm with decision-making thought is applied to the filtering process of the system,so as to improve the positioning accuracy of the whole system.Then,under the precondition of precise positioning,the path tracking method of indoor UAVs is further studied.On the basis of the traditional method,this paper fully considers the time-varying characteristics of the indoor environment.For the dynamic obstacles that may occur during path tracking,this paper proposes a path tracking method based on dynamic obstacle avoidance,thus realizing the autonomous navigation of the indoor unmanned aerial vehicle.This method is mainly composed of two major core modules: collision prediction and dynamic obstacle avoidance.In the collision prediction module,on the basis of the traditional virtual repulsion field,with full consideration of the dynamic obstacle movement,this paper proposed for the first time that the prediction of collision probability between UAVs and obstacle can be realized through the elliptical artificial potential field method,and perform the corresponding operation according to the forecast results;Then,the UAV performs the corresponding behavior pattern according to different results: When the UAV performs the dynamic collision avoidance action,the system realizes the selection of the target point according to the given safety function and uses it as the target point of the portion path planning to complete the obstacle avoidance task.In order to reduce the interference caused by the dynamic obstacle to the path planning,this paper proposes a rule to modify the grid confidence with the dynamic obstacle taking into account,thus improving the efficiency of the algorithm and the stability of the planning path;When the UAV performs a continuation path tracking action,UAV completes the tracking mission in accordance with the original expected path.Through the two core modules,the navigation and path tracking functions of UAV in the actual flight can be realized.Finally,the relevant experiments are completed through the simulation environment built by experimental platform.UAV High-precision positioning and dynamic path tracking are achieved in a complex dynamic environment.