Model-based constraints for trajectory determination of quad-copters: Design, calibration & merits for direct orientation

Abstract

This paper proposes a novel method to improve georeferencing of airborne laser scanning by improved trajectory estimation using Vehicle Dynamic Model. In Vehicle Dynamic Model (VDM), the relationship between the dynamics of the platform and control inputs is used as additional observations for sensor fusion. This relationship is available for most platforms and can be used without the need for additional hardware. However, this relationship is modeled using parameters that are a priori unknown. The proposed in-flight calibration methodology can achieve less than 2% error in the estimated model parameters compared to the values used in simulation. The effect of Inertial Measurement Unit (IMU) noise on the accuracy of airborne laser scanning is further investigated to demonstrate the reduction in the position error of georeferenced points when VDM measurements are used. The results are evaluated through a Monte-Carlo simulation involving an open-source autopilot. The reduction in the error of the estimated attitude due to vehicle modeling increases with the higher intensity of time-correlated IMU noise. Using a higher quality inertial sensor does not lead to an improvement in the position error of georeferenced points when VDM measurements are employed; however, a lower quality Inertial Measurement Unit, such as those on an autopilot, shows a 33% and 46% reduction in the mean and standard deviation of the position error of the georeferenced points, respectively.

Keywords

• Vehicle dynamic model
• Quad-copter
• Dynamic network
• Airborne laser scanning