Abstract

This paper addresses the key aspects of the sensor orientation and calibration approach within the mapKITE concept for corridor mapping, focusing on the contribution analysis of point-and-scale measurements of kinematic ground control points. MapKITE is a new mobile, simultaneous terrestrial and aerial, geodata acquisition and post-processing method. On one hand, the acquisition system is a tandem composed of a terrestrial mobile mapping system and an unmanned aerial system, the latter equipped with a remote sensing payload, and linked through a 'virtual tether', that is, a real-time waypoint supply from the terrestrial vehicle to the unmanned aircraft. On the other hand, mapKITE entails a method for geodata post-processing (specifically, sensor orientation and calibration) based on the described acquisition paradigm, focusing on few key aspects: the particular geometric relationship of a mapKITE network – the aerial vehicle always observes the terrestrial one as they both move –, precise air and ground trajectory determination – the terrestrial vehicle is regarded as a kinematic ground control point – and new photogrammetric measurements – pointing on and measuring the scale of an optical target on the roof of the terrestrial vehicle – are exploited. <br><br> In this paper, we analyze the performance of aerial image orientation and calibration in mapKITE for corridor mapping, which is the natural application niche of mapKITE, based on the principles and procedures of integrated sensor orientation with the addition of point-and-scale photogrammetric measurements of the kinematic ground control points. To do so, traditional (static ground control points, photogrammetric tie points, aerial control) and new (pointing-and-scaling of kinematic ground control points) measurements have been simulated for mapKITE corridor mapping missions, consisting on takeoff and calibration pattern, single-pass corridor operation potentially performing calibration patterns, and landing and calibration pattern. Our preliminary results show that the exterior orientation, interior orientation and tie points precision estimates are better when using kinematic control with few static ground control, and even with excluding the latter. We conclude then that mapKITE can be a breakthrough on the UAS-based corridor mapping field, as precision requirements can be achieved for single-pass operation with no need for traditional static ground control points.

Highlights

  • Unmanned Aerial Systems (UAS) have come to stay among the mapping community (Colomina and Molina, 2014)

  • Several UAS have established themselves as must-have surveyor tools (Sensefly’s Swinglet or eBee, Trimble’s UX-5 or Ascending Technologies’ Falcon-8) and even some consumer-grade platforms are being integrated into the mapping field; e.g., Phantom DJI’s via Pix4D tools

  • Regarding urban and inter-urban scenarios, high-resolution mapping has been recently performed with Terrestrial Mobile Mapping Systems (TMMS) equipped with cameras and/or LiDAR sensors, able to produce 3D geoinformation with high resolution and accuracy relying on direct sensor orientation by means of navigation-grade inertial and GNSS systems

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Summary

INTRODUCTION

Unmanned Aerial Systems (UAS) have come to stay among the mapping community (Colomina and Molina, 2014). To this respect, efforts in fusing Unmanned Aircraft (UA) images with terrestrial images (Puschel et al, n.d.), (Mayer, 2015), or combining 3D models based on UAS images with terrestrial LiDAR ones (Optech, 2015), indicate the feasibility of such an approach to achieve the total point of view from a mapping perspective. While current work by mapping companies (SenseFly, 2015), (Delair Tech, 2014) are based on the former, recent research explores the use of precise position and attitude aerial control to perform direct sensor orientation in corridor blocks (Rehak and Skaloud, 2015). The Fast AT concept was explored for corridor mapping in (Blazquez and Colomina, 2012), based again on precise position and attitude.

THE MAPKITE ESSENTIALS
SENSOR ORIENTATION AND CALIBRATION APPROACH
SIMULATED CORRIDORS AND RESULTS
Block design
Precision of measurements
Software
Simulated configurations
Simulation results
SUMMARY AND PRELIMINARY CONCLUSIONS
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