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UAV-based 3D Mapping
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UAV-based 3D Mapping

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Remote Sensors".

Deadline for manuscript submissions: closed (30 August 2019) | Viewed by 13848

Special Issue Editors

Prof. Dr. Ayman F. Habib

E-Mail Website
Guest Editor
Lyles School of Civil Engineering, Purdue University, West Lafayette, IN 47907, USA
Interests: photogrammetry; laser scanning; mobile mapping systems; system calibration; computer vision; unmanned aerial mapping systems; multisensor/multiplatform data integration
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Antonio Vettore

E-Mail Website
Guest Editor
Interdepartmental Research Center of Geomatics (CIRGEO), University of Padova, via dell’Università 16, 35020 Legnaro (PD), Italy
Interests: geomatics; mobile mapping; laser scanning; photogrammetry; remote sensing; navigation; unmanned aerial vehicles; cultural heritage; GIS
Special Issues, Collections and Topics in MDPI journals
Dr. Andrea Masiero

E-Mail Website
Guest Editor
Interdepartmental Research Center of Geomatics (CIRGEO), University of Padua, via dell' Università 16, 35020 Legnaro, PD, Italy
Interests: mobile mapping; geomatics; indoor and outdoor positioning and navigation; photogrammetry; laser scanning; machine learning; computer vision; remote sensing; adaptive optics; atmospheric turbulence
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The continuous developments in direct geo-referencing (i.e., integrated global navigation satellite systems (GNSS) and inertial navigation systems (INS)) and remote sensing (i.e., passive and active imaging sensors in the visible and infrared range of the electromagnetic spectrum – RGB/multi-spectral/hyperspectral cameras and laser scanning) are providing the professional geospatial community with ever-growing opportunities to generate accurate 3D information with rich sets of attributes. These advances are also coupled with improvements in the sensors’ performance, reduction in the associated cost, and miniaturization of such sensors. Aside from the sensing systems, we are also enjoying the emergence of promising platforms such as unmanned airborne vehicles (UAVs). UAVs equipped with consumer-grade imaging, ranging, and direct geo-referencing systems have proven to be a potential remote sensing platform that could satisfy the needs of a wide range of civilian applications. The advantages of UAV-based mapping can be attributed to the following facts: a) they can fly at lower elevation and slower speed than manned aircrafts, thus, providing high-quality spatial data; b) they can be cost-effectively stored and deployed, which make them optimal for rapid response applications; c) they are easy to use with minimal training requirements; d) they can provide repetitive mapping at higher frequency with minimal cost; and e) they are less affected by weather conditions (e.g., they can fly under cloud cover).

The aim of this Special Issue is to present the state-of-the-art research and development in the area of UAV-based mapping. We would like to invite contributions to the following topics (but it is not limited to them):

  • Passive and/or active sensor integration for UAV-based mapping
  • System calibration of multi-sensor UAV-based remote sensing
  • Optimization of UAV payload for remote sensing purposes
  • Direct geo-referencing of UAV systems
  • UAVs-based applications (e.g., precision agriculture, geometric documentation of transportation corridors, infrastructure monitoring, crash scene documentation, etc.)
  • Multi-sensor/multi-platform/temporal registration of UAV-based geospatial data
  • UAV-based mapping in GNSS-denied environments
  • Integration of UAV-based geospatial data with other remote sensing modalities
  • Quality control of UAV-based mapping products
  • 3D object detection and recognition from UAV-based geospatial products
  • UAV-based hyperspectral remote sensing
  • LiDAR-based UAV 3D mapping
  • Dense point cloud generation from UAV-based imaging systems
  • Interactive visualization of multi-sensor/multi-platform UAV-based geospatial data

Prof. Dr. Ayman F. Habib
Prof. Dr. Antonio Vettore
Dr. Andrea Masiero
Guest Editors

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Keywords

  • Unmanned aerial vehicles (UAVs)
  • Unmanned aerial systems (UAS)
  • UAV-based remote sensing
  • Sensor integration
  • System calibration
  • Direct geo-referencing
  • Laser scanning
  • Automated aerial triangulation
  • Dense matching
  • Point cloud processing

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Published Papers (3 papers)

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Research

24 pages, 5411 KiB  
Article
Autonomous 3D Exploration of Large Structures Using an UAV Equipped with a 2D LIDAR
by Margarida Faria, António Sérgio Ferreira, Héctor Pérez-Leon, Ivan Maza and Antidio Viguria
Sensors 2019, 19(22), 4849; https://doi.org/10.3390/s19224849 - 8 Nov 2019
Cited by 15 | Viewed by 4626
Abstract
This paper addressed the challenge of exploring large, unknown, and unstructured industrial environments with an unmanned aerial vehicle (UAV). The resulting system combined well-known components and techniques with a new manoeuvre to use a low-cost 2D laser to measure a 3D structure. Our [...] Read more.
This paper addressed the challenge of exploring large, unknown, and unstructured industrial environments with an unmanned aerial vehicle (UAV). The resulting system combined well-known components and techniques with a new manoeuvre to use a low-cost 2D laser to measure a 3D structure. Our approach combined frontier-based exploration, the Lazy Theta* path planner, and a flyby sampling manoeuvre to create a 3D map of large scenarios. One of the novelties of our system is that all the algorithms relied on the multi-resolution of the octomap for the world representation. We used a Hardware-in-the-Loop (HitL) simulation environment to collect accurate measurements of the capability of the open-source system to run online and on-board the UAV in real-time. Our approach is compared to different reference heuristics under this simulation environment showing better performance in regards to the amount of explored space. With the proposed approach, the UAV is able to explore 93% of the search space under 30 min, generating a path without repetition that adjusts to the occupied space covering indoor locations, irregular structures, and suspended obstacles. Full article
(This article belongs to the Special Issue UAV-based 3D Mapping)
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18 pages, 2176 KiB  
Article
Indoor Mapping Guidance Algorithm of Rotary-Wing UAV Including Dead-End Situations
by Jongho Park and Jaehyun Yoo
Sensors 2019, 19(22), 4854; https://doi.org/10.3390/s19224854 - 7 Nov 2019
Cited by 2 | Viewed by 2476
Abstract
A mapping guidance algorithm of a quadrotor for unknown indoor environments is proposed. A sensor with limited sensing range is assumed to be mounted on the quadrotor to obtain object data points. With obtained data, the quadrotor computes velocity vector and yaw commands [...] Read more.
A mapping guidance algorithm of a quadrotor for unknown indoor environments is proposed. A sensor with limited sensing range is assumed to be mounted on the quadrotor to obtain object data points. With obtained data, the quadrotor computes velocity vector and yaw commands to move around the object while maintaining a safe distance. The magnitude of the velocity vector is also controlled to prevent a collision. The distance transform method is applied to establish dead-end situation logic as well as exploration completion logic. When a dead-end situation occurs, the guidance algorithm of the quadrotor is switched to a particular maneuver. The proposed maneuver enables the quadrotor not only to escape from the dead-end situation, but also to find undiscovered area to continue mapping. Various numerical simulations are performed to verify the performance of the proposed mapping guidance algorithm. Full article
(This article belongs to the Special Issue UAV-based 3D Mapping)
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21 pages, 3360 KiB  
Article
UAV-Based Digital Terrain Model Generation under Leaf-Off Conditions to Support Teak Plantations Inventories in Tropical Dry Forests. A Case of the Coastal Region of Ecuador
by Fernando J. Aguilar, José R. Rivas, Abderrahim Nemmaoui, Alberto Peñalver and Manuel A. Aguilar
Sensors 2019, 19(8), 1934; https://doi.org/10.3390/s19081934 - 25 Apr 2019
Cited by 29 | Viewed by 5739
Abstract
Remote sensing is revolutionizing the way in which forests studies are conducted, and recent technological advances, such as Structure from Motion (SfM) photogrammetry from Unmanned Aerial Vehicle (UAV), are providing more efficient methods to assist in REDD (Reducing Emissions from Deforestation and forest [...] Read more.
Remote sensing is revolutionizing the way in which forests studies are conducted, and recent technological advances, such as Structure from Motion (SfM) photogrammetry from Unmanned Aerial Vehicle (UAV), are providing more efficient methods to assist in REDD (Reducing Emissions from Deforestation and forest Degradation) monitoring and forest sustainable management. The aim of this work was to develop and test a methodology based on SfM from UAV to generate high quality Digital Terrain Models (DTMs) on teak plantations (Tectona grandis Linn. F.) situated in the Coastal Region of Ecuador (dry tropical forest). UAV overlapping images were collected using a DJI Phantom 4 Advanced© quadcopter during the dry season (leaf-off phenological stage) over 58 teak square plots of 36 m side belonging to three different plantations located in the province of Guayas (Ecuador). A workflow consisting of SfM absolute image alignment based on field surveyed ground control points, very dense point cloud generation, ground points filtering and outlier removal, and DTM interpolation from labeled ground points, was accomplished. A very accurate Terrestrial Laser Scanning (TLS) derived ground points were employed as ground reference to estimate the UAV-SfM DTM vertical error in each reference plot. The plot-level obtained DTMs presented low vertical bias and random error (−3.1 cm and 11.9 cm on average, respectively), showing statistically significant greater error in those reference plots with basal area and estimated vegetation coverage above 15 m2/ha and 60%, respectively. To the best of the authors’ knowledge, this is the first study aimed at monitoring of teak plantations located in dry tropical forests from UAV images. It provides valuable information that recommends carrying out the UAV image capture during the leaf-off season to obtain UAV-SfM derived DTMs suitable to serve as ground reference in supporting teak plantations inventories. Full article
(This article belongs to the Special Issue UAV-based 3D Mapping)
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