自适应视觉惯性地磁紧耦合定位系统OA北大核心CSTPCD

To solve the problem of missing absolute heading data and attitude drift in the visual-inertial navigation system,and to enhance its positioning accuracy,an adaptive visual-inertial-geomagnetic tightly integrated positioning system was developed for environments with unknown magnetic fields.Initially,the calibration process for the internal and external parameters of standard tri-axis magnetometers is detailed.Following this,a strategy for generating global and frame-to-frame constrained residuals from geomagnetic data is outlined.The system dynamically adjusts fusion weights based on variations in magnetic intensity and employs a nonlinear optimization approach for the visual-inertial-geomagnetic integration to estimate its motion state accurately.Outdoor tests conducted on a university campus demonstrated that the system remains stable amidst magnetic disturbances from buildings and vehicles,achieving positioning accuracy better than 0.8%(RMSE).When compared to VINS,this system reduces position error by an average of 24%,showcasing impressive real-time capabilities.Incorporating magnetometers and adaptive fusion tech-niques significantly boosts the performance of existing visual-inertial navigation systems,offering reliable real-time positioning for autonomous systems.