Abstract

Abstract. This study highlights the benefits of precise aerial position and attitude control in the context of mapping with Micro Aerial Vehicles (MAVs). Accurate mapping with MAVs is gaining importance in applications such as corridor mapping, road and pipeline inspections or mapping of large areas with homogeneous surface structure, e.g. forests or agricultural fields. There, accurate aerial control plays a major role in successful terrain reconstruction and artifact-free ortophoto generation. The presented experiments focus on new approaches of aerial control. We confirm practically that the relative aerial position and attitude control can improve accuracy in difficult mapping scenarios. Indeed, the relative orientation method represents an attractive alternative in the context of MAVs for two reasons. First, the procedure is somewhat simplified, e.g. the angular misalignment, so called boresight, between the camera and the inertial measurement unit (IMU) does not have to be determined and, second, the effect of possible systematic errors in satellite positioning (e.g. due to multipath and/or incorrect recovery of differential carrier-phase ambiguities) is mitigated. First, we present a typical mapping project over an agricultural field and second, we perform a corridor road mapping. We evaluate the proposed methods in scenarios with and without automated image observations. We investigate a recently proposed concept where adjustment is performed using image observations limited to ground control and check points, so called fast aerial triangulation (Fast AT). In this context we show that accurate aerial control (absolute or relative) together with a few image observations can deliver accurate results comparable to classical aerial triangulation with thousands of image measurements. This procedure in turns reduces the demands on processing time and the requirements on the existence of surface texture. Finally, we compare the above mentioned procedures with direct sensor orientation (DiSO) to show its potential for rapid mapping.

Highlights

  • Unmanned aerial vehicles (UAVs) have become an important tool for surveyors, constructions engineers and scientists worldwide

  • This paper aimed at testing novel observation models in the context of Micro Aerial Vehicles (MAVs)

  • The initial part discussed the general problematic of sensor orientation with a specific focus on accurate mapping of difficult areas

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Summary

INTRODUCTION

Unmanned aerial vehicles (UAVs) have become an important tool for surveyors, constructions engineers and scientists worldwide. Thanks to their affordability and recent advances in guidance, autonomy and easiness of use, they spread among wide public. The number of available system is increasing rapidly (Colomina and Molina, 2014) This progress is accelerated by accompanied software bundled with the platforms that makes image processing as easy as never before. Despite this progress, indirect sensor orientation is still the most common way of sensor orientation (SO) in spite of a gradual rise up of commercial platforms with embedded systems offering at least accurate aerial position control (Mavinci, 2015, senseFly, 2015)

Concepts of sensor orientation
MAV-specific challenges
Paper structure
Absolute position and attitude control
Relative position and attitude control
Stochastic models of relative aerial control
Implementation
PERFORMANCE ANALYSIS
MAV platform and sensors
System calibration
Test data
Processing strategy
PRACTICAL EVALUATION
CONCLUSION AND PERSPECTIVES
Full Text
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