We discuss the evolution and state-of-the-art of the use of Unmanned Aerial Systems (UAS) in the field of Photogrammetry and Remote Sensing (PaRS). UAS, Remotely-Piloted Aerial Systems, Unmanned Aerial Vehicles or simply, drones are a hot topic comprising a diverse array of aspects including technology, privacy rights, safety and regulations, and even war and peace. Modern photogrammetry and remote sensing identified the potential of UAS-sourced imagery more than thirty years ago. In the last five years, these two sister disciplines have developed technology and methods that challenge the current aeronautical regulatory framework and their own traditional acquisition and processing methods. Navety and ingenuity have combined off-the-shelf, low-cost equipment with sophisticated computer vision, robotics and geomatic engineering. The results are cm-level resolution and accuracy products that can be generated even with cameras costing a few-hundred euros. In this review article, following a brief historic background and regulatory status analysis, we review the recent unmanned aircraft, sensing, navigation, orientation and general data processing developments for UAS photogrammetry and remote sensing with emphasis on the nano-micro-mini UAS segment.

https://cyberleninka.org/article/n/529930.pdf

Unmanned aerial systems for photogrammetry and remote sensing: A review

A scheme is developed for classifying the types of motion perceived by a humanlike robot. It is assumed that the robot receives visual images of the scene using a perspective system model. Equations, theorems, concepts, clues, etc., relating the objects, their positions, and their motion to their images on the focal plane are presented. >

http://ieeexplore.ieee.org/iel2/815/3148/00100651.pdf

Robot vision

This paper presents a survey of the autopilot systems for small or micro unmanned aerial vehicles (UAVs). The objective is to provide a summary of the current commercial, open source and research autopilot systems for convenience of potential small UAV users. The UAV flight control basics are introduced first. The radio control system and autopilot control system are then explained from both the hardware and software viewpoints. Several typical off-the-shelf autopilot packages are compared in terms of sensor packages, observation approaches and controller strengths. Afterwards some open source autopilot systems are introduced. Conclusion is made with a summary of the current autopilot market and a remark on the future development.

/pdf/autopilots-for-small-unmanned-aerial-vehicles-a-survey-5ap69uey7g.pdf

Autopilots for small unmanned aerial vehicles: A survey

This paper presents a survey of the autopilot systems for small fixed-wing unmanned air vehicles (UAVs). The UAV flight control basics are introduced first. The radio control system and autopilot control system are then explained from both hardware and software viewpoints. Several typical commercial off-the-shelf autopilot packages are compared in detail. In addition, some research autopilot systems are introduced. Finally, conclusions are made with a summary of the current autopilot market and a remark on the future development.This paper presents a survey of the autopilot systems for small fixed-wing unmanned air vehicles (UAVs). The UAV flight control basics are introduced first. The radio control system and autopilot control system are then explained from both hardware and software viewpoints. Several typical commercial off-the-shelf autopilot packages are compared in detail. In addition, some research autopilot systems are introduced. Finally, conclusions are made with a summary of the current autopilot market and a remark on the future development.

Autopilots for Small Fixed-Wing Unmanned Air Vehicles: A Survey

This paper presents a complete review of computer vision algorithms and vision-based intelligent applications, that are developed in the field of the Unmanned Aerial Vehicles (UAVs) in the latest decade. During this time, the evolution of relevant technologies for UAVs; such as component miniaturization, the increase of computational capabilities, and the evolution of computer vision techniques have allowed an important advance in the development of UAVs technologies and applications. Particularly, computer vision technologies integrated in UAVs allow to develop cutting-edge technologies to cope with aerial perception difficulties; such as visual navigation algorithms, obstacle detection and avoidance and aerial decision-making. All these expert technologies have developed a wide spectrum of application for UAVs, beyond the classic military and defense purposes. Unmanned Aerial Vehicles and Computer Vision are common topics in expert systems, so thanks to the recent advances in perception technologies, modern intelligent applications are developed to enhance autonomous UAV positioning, or automatic algorithms to avoid aerial collisions, among others. Then, the presented survey is based on artificial perception applications that represent important advances in the latest years in the expert system field related to the Unmanned Aerial Vehicles. In this paper, the most significant advances in this field are presented, able to solve fundamental technical limitations; such as visual odometry, obstacle detection, mapping and localization, et cetera. Besides, they have been analyzed based on their capabilities and potential utility. Moreover, the applications and UAVs are divided and categorized according to different criteria.

Survey of computer vision algorithms and applications for unmanned aerial vehicles

We develop a method for estimating the flight critical parameters of pitch angle, roll angle and the three body rates using horizon detection and optical flow. We achieve this through the use of an image processing front-end to detect candidate horizon lines through the use of morphological image processing and the Hough transform. The optical flow of the image for each candidate line is calculated, and using these measurements, we are able to estimate the body rates of the aircraft. Using an Extended Kalman Filter (EFK), the candidate horizon lines are propagated and tracked through successive image frames, with statistically unlikely horizon candidates eliminated.

Results qualitativly describing the performance of the image processing front-end on real datasets are presented, followed by an analysis of the improvement when utilising the motion model of the vehicle.

Attitude Estimation for a Fixed-Wing Aircraft Using Horizon Detection and Optical Flow

The last decade has seen a dramatic expansion in the deployment of Unmanned Airborne Vehicles (UAVs) as witnessed by deployments to Bosnia, Afghanistan and Iraq. Many low-cost UAVs operate without redundant attitude sensors and are therefore highly vulnerable to the failure of such sensors. 

It is common for low-cost UAVs to carry a vision sensor as its primary payload. Given that a human pilot is trained to control an aircraft with respect to a visual horizon under Visual Meteorological Conditions (VMC), it is logical to suggest that a similar capability be developed for a UAV in the event of the failure of the primary attitude system. In addition, it potentially gives the capability to estimate the attitude of a gimballed camera, without specifically equipping the gimballed platform with an angular sensor.

In this paper, we develop a method for estimating the flight critical parameters of pitch angle, roll angle and the three body rates using horizon detection and optical flow. We achieve this through the use of an image processing front-end to detect candidate horizon lines through the use of morphological image processing and the Hough transform. The optical flow of the image for each candidate line is calculated, and using these measurements, we are able to estimate the body rates of the aircraft. Using an Extended Kalman Filter (EFK), the candidate horizon lines are propagated and tracked through successive image frames, with statistically unlikely horizon candidates eliminated. 

Results are shown for a number of different datasets taken with cameras ranging from low-cost webcams to high-quality machine vision cameras are presented. Preliminary results show that although the front-end is adequate in many different scenarios, utilising temporal information results in a more robust performance of the detection algorithm which is well suited for use in attitude estimation.

Fixed-Wing Attitude Estimation Using Computer Vision Based Horizon Detection

We develop a method for estimating the flight critical parameters of pitch angle, roll angle and the three body rates using horizon detection and optical flow We achieve this through the use of an image processing front-end to detect candidate horizon lines through the use of morphological image processing and the Hough transform The optical flow of the image for each candidate line is calculated, and using these measurements, we are able to estimate the body rates of the aircraft Using an Extended Kalman Filter (EFK), the candidate horizon lines are propagated and tracked through successive image frames, with statistically unlikely horizon candidates eliminated Results qualitativly describing the performance of the image processing front-end on real datasets are presented, followed by an analysis of the improvement when utilising the motion model of the vehicle

/pdf/attitude-estimation-for-a-fixed-wing-aircraft-using-horizon-32j4qp6b87.pdf

Surveying system for measuring the position of a measuring point on the ground is disclosed. The surveying system may include a survey pole with a body having a pointer tip for contacting the measuring point and position giving means for making available the coordinative determination of a referenced position, being placed on the body with a defined spatial relationship relative to the tip. Determination means may be included for repeatedly determining the referenced position of the position giving means. Evaluation means may also be included for deriving the position of the measuring point. In some embodiments, the survey pole may also include an inertial measuring unit placed on the body with a defined spatial relationship relative to the position giving means.

Surveying System and Method

In this paper, we present a method for the recovery of position and absolute attitude (including pitch, roll and yaw) using a novel fusion of monocular visual odometry and GPS measurements in a similar manner to a classic loosely coupled GPS/INS error state navigation filter. The proposed filter does not require additional restrictions or assumptions such as platform-specific dynamics, map matching, feature tracking, visual loop closing, gravity vector or additional sensors such as an inertial measurement unit or magnetic compass. An observability analysis of the proposed filter is performed, showing that the scale factor, position and attitude errors are fully observable under acceleration that is non-parallel to the velocity vector in the navigation frame. The observability properties of the proposed filter are demonstrated using numerical simulations. We conclude the article with an implementation of the proposed filter using real flight data collected from a Cessna 172 equipped with a downwards-looking camera and GPS, showing the feasibility of the algorithm in real-world conditions.

/pdf/error-analysis-and-attitude-observability-of-a-monocular-gps-oscxu6q9pi.pdf

Damien Dusha

Papers

Attitude Estimation for a Fixed-Wing Aircraft Using Horizon Detection and Optical Flow

Fixed-Wing Attitude Estimation Using Computer Vision Based Horizon Detection

Attitude Estimation for a Fixed-Wing Aircraft Using Horizon Detection and Optical Flow

Surveying System and Method

Error analysis and attitude observability of a monocular GPS/visual odometry integrated navigation filter