Special Issue "UAS Navigation and Orientation"

A special issue of Drones (ISSN 2504-446X).

Deadline for manuscript submissions: closed (30 June 2019).

Special Issue Editors

Dr. Costas Armenakis
Website
Guest Editor
Associate Professor and Program Director, Geomatics Engineering, Department of Earth and Space Science and Engineering, Lassonde School of Engineering, York University, Ontario, Canada
Interests: photogrammetric engineering and remote sensing mapping, low-cost unmanned mobile mapping systems with focus on the use of unmanned aerial mapping systems for geomatics, indoor/outdoor navigation and mapping, sensor integration, 3D modelling using optical and lidar data, mapping from high resolution imagery, image-sequence for mapping and scene analysis, spatial data co-registration, spatial awareness and intelligence, integration of GIS and remote sensing methods, risk assessment and disaster management
Dr. Ismael Colomina
Website
Guest Editor
GeoNumerics, Castelldefels, Spain
Interests: geomatics; navigation; geometric photogrammetry and remote sensing; sensor modelling; sensor integration; sensor orientation and calibration; multi-sensor integration for orientation and navigation; indoor/outdoor navigation; estimation methods; software systems for orientation and navigation; unmanned aerial systems; unmanned aerial systems for photogrammetry, remote sensing and mapping; combined terrestrial and aerial mobile mapping systems

Special Issue Information

Dear Colleagues,

The trend to develop semi-autonomous and autonomous Unmanned Aircraft System (UAS) continues to accelerate. Accurate and ubiquitous UAS navigation and orientation, and UAS high-definition mapping are challenging tasks towards fully-automated and autonomous operations. Currently, no single technology allows the accurate and reliable determination of the position of a UAS at all times. Autonomous flying of a UAS in known and unknown environments requires continuous integration of the navigation sensors data, perception of environmental elements with respect to space and time, understanding of the scene situation through data and information, anticipation of next stages, and ability to make quick knowledge-based decisions based on real-time position and navigation, scene sensing, recognition, understanding and visualization.

The navigation and orientation of UAS provide position, velocity and attitude of the flying platform and its payload sensors within a reference system. These are critical aspects in determining accurately the dynamic state of the platform, its trajectory and route to destination, and in mapping the environment from data captured by the onboard mapping sensors. Navigation, a real-time task, is a critical element of UAS route planning and obstacle sense and avoidance as the UAS explores its surroundings, matching the scene with given databases, detecting and analyzing scene-database differences, “learning” through exploration and understanding and selecting a route based on certain criteria and constraints. Orientation, a post-mission task, is critical in the optimal exploitation of the remotely sensed data for the purposes of sensor position and attitude determination, sensor calibration and sensor synchronization.

This Special Issue focuses on novel and innovative methods and approaches for determining the position, velocity and attitude of the UAS for applications as overarching as input to the autopilots, simultaneous localization and mapping down to very accurate post-mission sensor fusion algorithms for orientation determination. We welcome submissions which provide the community with the most recent advancements on all aspects of UAV Navigation and Orientation, including but not limited to:

  • Direct, indirect and integrated sensor/platform positioning and orientation
  • Vision-based navigation and orientation
  • Single/multiple IMU–Vision-based navigation and orientation
  • Simultaneous Localization and Mapping (SLAM)
  • Navigation and orientation using machine learning and deep learning
  • Kalman and Particle filtering and other advanced techniques for motion sensor data fusion
  • Computational aspects and incremental approaches
  • Collaborative UAS-UAS and UAS-UGV missions
  • Navigation and orientation in outdoors and indoors environments
  • Autonomous navigation
  • Obstacle detection and avoidance
  • Precise Point Positioning (PPP) navigation
  • Ultra Wide Band (UWB) localization
  • Optical flow–based vision-based navigation
  • Trajectory tracking systems
  • Autopilots and navigation: standard and advanced solutions for navigation integrity
  • Path planning
  • Beyond visual line of sight (BVLOS) navigation

Dr. Costas Armenakis
Dr. Ismael Colomina
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Drones is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (4 papers)

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Research

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Open AccessArticle
Photometric Long-Range Positioning of LED Targets for Cooperative Navigation in UAVs
Drones 2019, 3(3), 69; https://doi.org/10.3390/drones3030069 - 30 Aug 2019
Abstract
Autonomous flight with unmanned aerial vehicles (UAVs) nowadays depends on the availability and reliability of Global Navigation Satellites Systems (GNSS). In cluttered outdoor scenarios, such as narrow gorges, or near tall artificial structures, such as bridges or dams, reduced sky visibility and multipath [...] Read more.
Autonomous flight with unmanned aerial vehicles (UAVs) nowadays depends on the availability and reliability of Global Navigation Satellites Systems (GNSS). In cluttered outdoor scenarios, such as narrow gorges, or near tall artificial structures, such as bridges or dams, reduced sky visibility and multipath effects compromise the quality and the trustworthiness of the GNSS position fixes, making autonomous, or even manual, flight difficult and dangerous. To overcome this problem, cooperative navigation has been proposed: a second UAV flies away from any occluding objects and in line of sight from the first and provides the latter with positioning information, removing the need for full and reliable GNSS coverage in the area of interest. In this work we use high-power light-emitting diodes (LEDs) to signalize the second drone and we present a computer vision pipeline that allows to track the second drone in real-time from a distance up to 100 m and to compute its relative position with decimeter accuracy. This is based on an extension to the classical iterative algorithm for the Perspective-n-Points problem in which the photometric error is minimized according to a image formation model. This extension allow to substantially increase the accuracy of point-feature measurements in image space (up to 0.05 pixels), which directly translates into higher positioning accuracy with respect to conventional methods. Full article
(This article belongs to the Special Issue UAS Navigation and Orientation)
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Open AccessArticle
Towards a Model Based Sensor Measurement Variance Input for Extended Kalman Filter State Estimation
Drones 2019, 3(1), 19; https://doi.org/10.3390/drones3010019 - 14 Feb 2019
Cited by 4
Abstract
In this paper, we present an alternate method for the generation and implementation of the sensor measurement variance used in an Extended Kalman Filter (EKF). Furthermore, it demonstrates the limitations of a conventional EKF implementation and postulates an alternate form for representing the [...] Read more.
In this paper, we present an alternate method for the generation and implementation of the sensor measurement variance used in an Extended Kalman Filter (EKF). Furthermore, it demonstrates the limitations of a conventional EKF implementation and postulates an alternate form for representing the sensor measurement variance by extending and improving the characterisation methodology presented in the previous work. As presented in earlier work, the use of surveying grade optical measurement instruments allows for a more effective characterisation of Ultra-Wide Band (UWB) localisation sensors; however, in cluttered environments, the sensor measurement variance will change, making this method not robust. To compensate for the noisier readings, an EKF using a model based sensor measurement variance was developed. This approach allows for a more accurate representation of the sensor measurement variance and leads to a more robust state estimation system. Simulations were run using synthetic data in order to test the effectiveness of the EKF against the originally developed EKF; next, the new EKF was compared to the original EKF using real world data. The new EKF was shown to function much more stably and consistently in less ideal environments for UWB deployment than the previous version. Full article
(This article belongs to the Special Issue UAS Navigation and Orientation)
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Open AccessArticle
Sensitivity to Time Delays in VDM-Based Navigation
Drones 2019, 3(1), 11; https://doi.org/10.3390/drones3010011 - 14 Jan 2019
Abstract
A recently proposed navigation methodology for aerial platforms based on the vehicle dynamic model (VDM) has shown promising results in terms of navigation autonomy. Its practical realization requires that control inputs are related to the same absolute time frame as inertial measurement unit [...] Read more.
A recently proposed navigation methodology for aerial platforms based on the vehicle dynamic model (VDM) has shown promising results in terms of navigation autonomy. Its practical realization requires that control inputs are related to the same absolute time frame as inertial measurement unit (IMU) data and all other observations when available (e.g., global navigation satellite system (GNSS) position, barometric altitude, etc.). This study analyzes the (non-) tolerances of possible delays in control-input command with respect to navigation performance on a fixed-wing unmanned aerial vehicle (UAV). Multiple simulations using two emulated trajectories based on real flights reveal the vital importance of correct time-tagging of servo data while that of motor data turned out to be tolerable to a considerably large extent. Full article
(This article belongs to the Special Issue UAS Navigation and Orientation)
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Review

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Open AccessReview
A Survey of Recent Extended Variants of the Traveling Salesman and Vehicle Routing Problems for Unmanned Aerial Vehicles
Drones 2019, 3(3), 66; https://doi.org/10.3390/drones3030066 - 24 Aug 2019
Cited by 2
Abstract
The use of Unmanned Aerial Vehicles (UAVs) is rapidly growing in popularity. Initially introduced for military purposes, over the past few years, UAVs and related technologies have successfully transitioned to a whole new range of civilian applications such as delivery, logistics, surveillance, entertainment, [...] Read more.
The use of Unmanned Aerial Vehicles (UAVs) is rapidly growing in popularity. Initially introduced for military purposes, over the past few years, UAVs and related technologies have successfully transitioned to a whole new range of civilian applications such as delivery, logistics, surveillance, entertainment, and so forth. They have opened new possibilities such as allowing operation in otherwise difficult or hazardous areas, for instance. For all applications, one foremost concern is the selection of the paths and trajectories of UAVs, and at the same time, UAVs control comes with many challenges, as they have limited energy, limited load capacity and are vulnerable to difficult weather conditions. Generally, efficiently operating a drone can be mathematically formalized as a path optimization problem under some constraints. This shares some commonalities with similar problems that have been extensively studied in the context of urban vehicles and it is only natural that the recent literature has extended the latter to fit aerial vehicle constraints. The knowledge of such problems, their formulation, the resolution methods proposed—through the variants induced specifically by UAVs features—are of interest for practitioners for any UAV application. Hence, in this study, we propose a review of existing literature devoted to such UAV path optimization problems, focusing specifically on the sub-class of problems that consider the mobility on a macroscopic scale. These are related to the two existing general classic ones—the Traveling Salesman Problem and the Vehicle Routing Problem. We analyze the recent literature that adapted the problems to the UAV context, provide an extensive classification and taxonomy of their problems and their formulation and also give a synthetic overview of the resolution techniques, performance metrics and obtained numerical results. Full article
(This article belongs to the Special Issue UAS Navigation and Orientation)
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