Research On Multi-sensor Autonomous Positioning And Path Planning Technology For Unmanned Platform

When the environment is unknown and the GNSS signal is weak and sometimes absent,the positioning accuracy of a single navigation method is not high and can not complete the established navigation task well.Taking the unmanned platform equipped with a variety of navigation sensors as the research object,this paper focuses on the autonomous positioning and mapping algorithm and the path planning method based on the artificial potential field method,for the reasons of improve the ability of autonomous positioning,mapping and path planning of the unmanned platform in the unknown environment.The main contents include:First of all,this paper briefly summarizes the theoretical basis of autonomous localization,mapping and path planning based on multi-sensor fusion.The camera imaging principle,the basic principle of vision system positioning and the principle of binocular ranging of vision navigation system are analyzed;The IMU measurement model and IMU pre integration of inertial navigation system are summarized;The architecture and protocol composition of global satellite navigation system and the composition architecture and positioning method of radio navigation system are analyzed in detail.Aiming at the problems that GNSS signal is vulnerable to interference and failure in complex outdoor environment,single navigation mode is not reliable,and the positioning accuracy is not high when unmanned platform carries out continuous and real-time navigation,a multi-sensor integrated navigation framework based on radio signal,visual odometer,inertial measurement unit and GNSS signal is proposed in this paper.The distance and angle information obtained by radio measurement is added to the traditional visual inertial GNSS navigation framework,and the integrated navigation architecture based on vision,inertia,GNSS and radio is established according to the obtained data;The obtained data are fused based on graph optimization method,and the measurement noise generated by multi-sensor is suppressed.Finally,the position and attitude of unmanned vehicle are estimated cooperatively.The experimental results on public data sets show the effectiveness of the proposed method.In the complex outdoor environment with unreliable GNSS,the positioning accuracy of the system is improved,the performance of the system is improved,and the system has good robustness.Aiming at the problems that GNSS signal is vulnerable to interference and failure in complex outdoor environment,single navigation mode is not reliable,and the positioning accuracy is not high when unmanned platform carries out continuous and real-time navigation,a multi-sensor integrated navigation framework based on radio signal,visual odometer,inertial measurement unit and GNSS signal is proposed in this paper.The distance and angle information obtained by radio measurement is added to the traditional visual inertial GNSS navigation framework,and the integrated navigation architecture based on vision,inertia,GNSS and radio is established according to the obtained data;The obtained data are fused based on graph optimization method,and the measurement noise generated by multi-sensor is suppressed.Finally,the position and attitude of unmanned vehicle are estimated cooperatively.The experimental results on public data sets show the effectiveness of the proposed method.In the complex outdoor environment with unreliable GNSS,the positioning accuracy of the system is improved,the performance of the system is improved,and the system has good robustness.An experimental verification system for autonomous positioning and navigation of unmanned platform equipped with a variety of navigation sensors is built,the hardware composition is introduced,and the sensor calibration is completed.Based on the core controller TX2 of unmanned platform,an embedded software of unmanned platform is designed and developed.The method in this paper is transplanted to TX2 processor to process and fuse multi-sensor information.Using T30 as the remote control terminal,the remote control software of unmanned platform is designed and developed.T30 displays the position information of unmanned platform and controls the movement of unmanned platform.In order to verify the integrated navigation method of multi-sensor fusion and the path planning method based on the improved artificial potential field method proposed in this paper,the positioning experiment under the unity virtual simulation scene,the actual outdoor scene positioning experiment based on the unmanned platform,the comparison experiment and effectiveness experiment of the actual outdoor scene path planning based on the unmanned platform are carried out,The experimental results show that the positioning method proposed in this paper has good positioning accuracy and robustness,and verify the effectiveness and reliability of the path planning method proposed in this paper.