UAV-Borne 3-D Mapping System by Multisensor Integration

Abstract

Abstract-To represent 3-D space in detail, it is necessary to acquire 3-D shapes and textures simultaneously and efficiently through the use of precise trajectories of sensors. However, there is no reliable, quick, cheap, and handy method for acquiring accurate high-resolution 3-D data on objects in outdoor and moving environments. In this paper, we propose a combination of charge-coupled device cameras, a small and inexpensive laser scanner, an inexpensive inertial measurement unit, and Global Positioning System for a UAV-borne 3-D mapping system. Direct georeferencing is achieved automatically using all of the sensors without any ground control points. A new method of direct georeferencing by the combination of bundle block adjustment and Kalman filtering is proposed. This allows objects to be rendered richly in shape and detailed texture automatically via a UAV from low altitude. This mapping system has been experimentally used in recovery efforts after natural disasters such as landslides, as well as in applications such as river monitoring.

Radiometric and Geometric Analysis of Hyperspectral Imagery Acquired from an Unmanned Aerial Vehicle

“…However, these low-cost hyperspectral systems require radiometric and geometric calibration to allow quantitative scientific analysis [17,18]. To date, several related studies have paired small, lightweight, rotary or fixed-wing UAV platforms with some combination of video, multi-band digital cameras, synthetic aperture radar (SAR), and laser scanning [19][20][21][22][23][24][25][26][27]. Yet, to our knowledge, few studies have successfully tested pushbroom hyperspectral sensors on small, lightweight, fixed-wing UAVs [28,29].…”

Realistic texture synthesis for point-based fruitage phenotype

“…Lingy Liu presented a texture mapping system that focuses on the accuracy problem of geometric transformation [31]. Starting from a point, Paul Rosenthal rendered the lit point clouds into texture with color, depth and normal information point-by-point [32], and UAV-borne 3-D mapping systems allowed objects to be rendered with rich shapes and detailed textures [33], but they all resulted in a dramatic performance decline as the point number increased. Using Wasserstein barycenters for point clouds in texture mixing has the additional requirement of averaging features and slicing approximation on each dimension distribution [34].…”

System Considerations and Challendes in 3d Mapping and Modeling Using Low-Cost Uav Systems

“…Alternatively, the use of large UAVs with heavier payloads, which can handle mapping-grade sensors, would sacrifice the cost benefit. Therefore, different research activities have been conducted in the past few years are to address the challenges arising from the use of lower-quality mapping sensors while maintaining the quality of the mapping outcome (Nagai et al, 2009;Pfeifer et al, 2012;Wallace et al, 2012;Rehak et al, 2013). The next important consideration in system architecture design is structural integrity and optimum arrangement of different sensors relative to each other to provide the required overlap between the collected data by these sensors.…”