1,721,033 research outputs found
RGB-D camera-based quadrotor navigation in GPS-denied and low light environments using known 3D markers
No full textThis paper presents an original approach for autonomous navigation based on RGB-D data and known 3D markers, where the basic concept is to detect and recognize the markers and then to use them for a straightforward pose estimation solution. The developed algorithms can allow a quadrotor to autonomously fly in (cooperative) GPS denied environments and/or when there is no natural or artificial illumination of the scene, by following a predetermined path consisting of successive targets having a well defined shape and/or color. Algorithms for target detection and recognition based on depth data are described which are optimized for real time use, paying particular attention to the on-board computational load. Experimental tests have been carried out by integrating a RGB-Depth sensor (ASUS Xtion Pro Live) on-board a custom-built quadrotor. First results confirm the potential of the proposed approach. The technique can be applied to different types of unmanned aerial vehicles (UAVs), as well as unmanned ground vehicles (UGVs)
PCA-Based Line Detection from Range Data for Mapping and Localization-Aiding of UAVs
Get PDFThis paper presents an original technique for robust detection of line features from range data, which is also the core element of
an algorithm conceived for mapping 2D environments. A new approach is also discussed to improve the accuracy of position and
attitude estimates of the localization by feeding back angular information extracted from the detected edges in the updating map.
The innovative aspects of the line detection algorithm regard the proposed hierarchical clusterization method for segmentation.
Instead, line fitting is carried out by exploiting the Principal Component Analysis, unlike traditional techniques relying on least
squares linear regression. Numerical simulations are purposely conceived to compare these approaches for line fitting. Results
demonstrate the applicability of the proposed technique as it provides comparable performance in terms of computational load
and accuracy compared to the least squares method. Also, performance of the overall line detection architecture, as well as of
the solutions proposed for line-based mapping and localization-aiding, is evaluated exploiting real range data acquired in indoor
environments using an UTM-30LX-EW 2D LIDAR. This paper lies in the framework of autonomous navigation of unmanned
vehicles moving in complex 2D areas, for example, being unexplored, full of obstacles, GPS-challenging, or denied
LIDAR-inertial integration for UAV localization and mapping in complex environments
No full textThis paper presents customized techniques for autonomous localization and mapping of micro Unmanned Aerial Vehicles flying in complex environments, e.g. unexplored, full of obstacles, GPS challenging or denied. The proposed algorithms are aimed at 2D environments and are based on the integration of 3D data, i.e. point clouds acquired by means of a laser scanner (LIDAR), and inertial data given by a low cost Inertial Measurement Unit (IMU). Specifically, localization is performed by exploiting a scan matching approach based on a customized version of the Iterative Closest Point algorithm, while mapping is done by extracting robust line features from LIDAR measurements. A peculiarity of the line detection method is the use of the Principal Component Analysis which allows computational time saving with respect to traditional least squares techniques for line fitting. Performance of the proposed approaches is evaluated on real data acquired in indoor environments by means of an experimental setup including an UTM-30LX-EW 2D LIDAR, a Pixhawk IMU, and a Nitrogen board
Implementation of a Distributed Flocking Algorithm with Obstacle Avoidance Capability for UAV Swarming
No full textAn implementation of a distributed flocking algorithm with obstacle avoidance capability for a swarm of UAVs is presented. Aim of the algorithm is to produce the accelerations to guide the flock in reaching its destination while avoiding obstacles and each other. The distributed nature of the algorithm consists in the capability of each component of the swarm to calculate its own acceleration while having only partial measurements, such as position and velocity, of only neighbouring vehicles. A limitation related to the strong assumptions that have to be made about the obstacles shape has been individuated in literature. The root cause has been identified and a possible solution has been investigated to overcome the restriction
Energy efficient wireless sensor network topologies and routing for structural health monitoring.
Get PDFThe applicability of wireless sensor networks (WSNs) has dramatically increased from the era of smart farming and environmental monitoring to the recent commercially successful internet of things (IoT) applications. Simultaneously, diversity in WSN applications has led to the application of specific performance requirements, such as fault tolerance, reliability, robustness and survivability. One important application is structural health monitoring (SHM) in airplanes.
Airborne Wireless Sensor Network (AWSN) have received considerable attention in recent times, owing to the many issues that are intrinsic to traditional wire-based airplane monitoring systems, such as complicated cable routing, long wiring, wiring degradation over time, installation overhead, etc. This project examines the SHM of aircraft wing and WSN design (ZigBee), and aspects such as node deployment and power efficient routing, vis-à-vis energy harvesting. Node deployment and power efficient routing protocol are related problems, and so this thesis proposes solutions using optimization techniques for Ant Colony Optimization (ACO), and power transmission profiling using Computer Simulation Technology software (CST).
There are three wing models; namely NACA64A410 model, Empty NACA64A410 model for the Wing, and Empty Prismatic model of the wing was specified and simulated in CST software. A simulation was carried out between the frequencies of 100 MHz to 5 GHz, and identified significant variations in the Sij parameter between the frequency range 2.4GHz and 2.5GHz. Critical analysis of the obtained results revealed the presence of a significant impact from wing
shape and the wing’s inner structure on possible radio wave propagation in the aircraft wing. The different material composition of aircraft wings was also examined to establish the influence of aircraft wing material on radio wave propagation in an aircraft wing. The three materials tested were Perfect Electrical Conductor (PEC), Aluminium, and Carbon Fibre Composites (CFCs). For power transmission profiling (Sij parameter), 130 nodes were deployed in regular and periodic compartments, created by ribs and spars, usually at vantage points and rib openings, so that a direct line of sight could be established. However, four sink nodes were also placed at the wing root, as presented in NC37 and NC38 simulations for aluminium and CFC wing models respectively. The evaluation of signal propagation in aluminium and CFC aircraft wing models revealed CFC wing models allow less transmission than aluminium wing models.
A multiple Travelling Salesman (mTSP) problem was formulated and solved, using Ant Colony Optimization in MATLAB to identify optimal topology and optimal routes to support radio propagation in ZigBee networks. Then solving the mTSP problem for different regular deployments of nodes in the wing geometry, it was found that an edgewise communication route was the shortest route for a large number of nodes, wherein 4 fixed sink nodes were placed at
the wing root. For a realistic wing model, the different possible configuration of ZigBee units were deduced using rational reasoning, based on results from empty wing models. Besides the determined S-parameter, aircraft wing materials and optimal nodes, the residual energy of each sensor node is also considered an essential criterion to improve the efficiency of ZigBee communications on the aircraft wing. Therefore, a novel hybrid protocol called the Energy-Opportunistic Weighted Minimum Energy (EOWEME) protocol can be formulated and implemented in MATLAB. The comparative results revealed the energy saving of EOWEME protocol is 20% higher compared to the Ad Hoc On-Demand Distance Vector (AODV) routing protocol. However, the need for further energy savings resulted in development of an improved EOWEME protocol when incorporating the clustering concept and the previously determined S-parameter, a number of nodes, and their radiation patterns. Critical evaluation of this improved EOWEME protocol showed a maximum of 10% higher energy savings than the previous EOWEME protocol.
To summarize key insights and the results of this thesis, it is apparent that the thesis addresses SHM in aircraft wings, using WSNs from a holistic perspective with the following major contributions,
• CST simulations identify power transfer (S-parameter) profiling in various wing models, with no internal structural elements to identify realistic wing with spars, and bars. With an average S-parameter of -107 dB at around 3 m, the communication or transmission range of 1 m was identified to minimize loss of transmitted power. A range less than 1m would cause issues such as interference, reflection etc.
• Using a transmission range of 1 m, WSN nodes were assessed for shortest route commensurate with energy efficient packet transmission to sink node from the farthest node; i.e. near the wing tip. The shortest routes converged to travel along the length of the wing in the case of an empty wing model, however it was also observed in a realistic wing model, where internal structural elements constrained node deployment. An average distance of nearly 13 m required data transmitted from the farthest nodes to reach the sink nodes. Increasing the nodes however increased the distance required to up to 20 m in the case of 240 nodes.
• A new routing protocol, EOWEME was formulated, showing 20% greater energy savings than AODV in the realistic wing model.PhD in Aerospac
Optimal energy management for electric aircraft.
Get PDFCurrent technological advances in aviation are geared towards a more "electric
aircraft"; seen as a step towards making the aircraft more efficient, reducing
emissions and minimising environmental impact. This thesis investigates the
feasibility of using an electric hybrid system consisting of a 1.2KW proton exchange
membrane fuel cell (PEMFC), three 12V lead acid batteries, a unidirectional stepdown
DC/DC converter, a bidirectional DC/DC converter to power a small aircraft.
Using this hybrid configuration the desired power for different flight phases could be
achieved. The advantage of PEMFCs is their high power density, low volume and
light weight. They operate at relatively low temperatures that allow them to start up
quickly without a warming up time. The thesis starts with a literature review of fuel
cell technology and a description of a simulation model for the hybrid system
developed using MATLAB/Simulink. Initial experimental results for model validation
and the system components performance characteristics will be presented. The
experimental data were obtained using 1.2kW Nexa power module FC.
With regards to the power management aspect, two control strategies have been
applied: (1) a traditional (PID) controller was designed and implemented in hardware-in-
the-loop to control the battery current via the bidirectional DC/DC converter in the
hybrid system, and, (2) replacing the PM controller with a fuzzy logic controller
(FLC), because significant time delays were found under PID control. The FLC was
implemented to manage the power between two sources in the hybrid system because
there are many reports in the literature of successful application of FLC to distribute
power between different sources in automotive applications. FLC design was based
on the following principle: the PEMFC is the main power supply for the electric
engine driving the propeller and it has to be operated at optimal efficiency. In the case
that the fuel cell cannot completely meet the power demands in any of the flight
phases, the battery will provide a short power burst demand as required. At the same
time the FC should keep the battery adequately charged at all times. The controller's
input variables are the electric engine power demand and battery state of charge
represented by the battery voltage. The output variable is the bidirectional DC/DC
converter output power. The use of a FLC allowed the system to operate at an optimal
efficiency, satisfying the aircraft's power demand during different flight phases.PhD in the School of Engineerin
Vision based landmark detection for UAV navigation
Get PDFThe majority of Unmanned Aerial Vehicles (UAV) available today depend on Global Position Satellites (GPS) and inertial measurement units (IMU) for state estimation used in navigation and control. However with the increase in availability of cheap GPS jamming technologies leads to concerns over the dependence of GPS for control and navigation. A possible solution is to use a downward looking camera on-board the aircraft, and using vision based techniques the aircraft can estimate its position without the need for GPS signals.
The focus of this thesis is to develop reliable methods for feature and landmark extraction for use with the vision based positioning system.
The first method proposed estimated the aircraft position in real time using Image Registration techniques, during testing it was found that it did not cope well if there are differences between the source and reference images, which could be due to seasonal or lighting changes. To overcome this problem, work was conducted to look at object detection (buildings, and roads) which enable objects to be detected despite changes in season, or lighting conditions. Three such methods are presented in this thesis, although all of them have been shown to work, only the Haar classifier based method is suitable for use on-board a UAV as the other methods are computationally intensive. Further testing of the Haar classifier was conducted to investigate the full envelope of the object detection under a simulated test.
Haar classifier cascade for object detection in aerial images was shown to be capable of detecting objects reliably under a variety of different situations in this thesis. This information can then be used with a GIS database to match the objects extracted from the image, with objects on a geo coded object database to estimate the aircraft position in a variety of different conditions
Vision-based Navigation Using Landmark Recognition for Unmanned Aerial Vehicles
Get PDFThis thesis describes a new approach for a vision-based positioning system for Un-
manned Aerial Vehicles using a recognition method based on known, robust geo-
graphic landmarks. Landmarks are used to calculate a position estimate in a global
coordinate frame without requiring external signals, such as GPS. Absolute systems
are of interest as they provide a redundant positioning system, allow UAVs to oper-
ate when GPS-denied and can enable high-precision landings for spacecraft.
The core challenge with vision-based absolute positioning is recognition of land-
marks. Most abundant landmarks, such as buildings, are visually similar and dif-
cult to distinguish. Previous research in the area tends to focus on matching raw
aerial image data to a set of reference images. While these methods can achieve
acceptable results in speci c conditions, they struggle with variations in lighting,
seasonal changes and changing environments. This thesis presents a new multi-
stage method that aims to solve this using a high-level matching framework where
landmarks identi ed in an aerial image are matched to a reference database.
This has led to the development of a geometric feature descriptor that encodes the
topography of landmarks. The proposed system therefore matches the arrangement
of features rather than the appearance, which lets it distinguish individual landmarks
in large sets (20,000+ features). Since the arrangement of landmarks often is semi-
structured and ambiguous, in particular when considering man-made landmarks,
a matching stage has been developed that uses a number of strategies to enable
matching of individual landmarks to a full database.
The results have been evaluated for two conceptual vehicles with acceptable results,
highlighting the strengths of the proposed system as well as areas for improve-
ment
Aircraft head-up display surface guidance system
Get PDFThe continues growth in aviation and passenger numbers is putting more
pressure on airports to become more efficient in order to reduce the number of
delays due to external factors such as weather, pilot deviation/errors and airport
maintenance traffic. As major hubs (e.g. Heathrow, New York or Paris) expand
in size to accommodate more traffic; aircraft surface movement and
management become more complex and the margin for error is even lower. The
traditional airport traffic management tools in large airports are increasingly
stretched to the limit in meeting safety and traffic throughput requirements. This
presents a huge challenge to the efficiency of airport operations because of the
increased number of departures and arrivals at those airports. New technology
for surface movement needs to be implemented in order to increase the safety
and airport capacity. The federal aviation authorities in the USA was first to
introduce the concept of Advanced Surface Movement Guidance and Control
System (A-SMGCS) to address this problem in commercial airdrome operations.
The system facilitates pilot recognition of the route designated by the traffic
controllers and uses warning information to make them aware of any potential
deviations/incursions. The system is introduced to enhance the efficiency of
surface movement by increasing the aircraft taxiing speed and reducing any
pilot errors during bad weather conditions.
This thesis focuses on the surface guidance system for aircraft equipped with
head-up display. A simulation model of the virtual environment using FlightGear
and Simulink is developed based on the study of a moving map and surface
guidance system for Head-Up Display (HUD) to assign the route, guide the
aircraft on the designated taxiway and avoid potential conflict with other aircraft.
A method of generating an airport in FlightGear and driving an airport moving
map to rotate and move is also illustrated which includes the data processing
flow chart and system flow chart. The Ordnance Survey National Grid and world
coordinate system is discussed and used to transform from GPS latitude and
longitude data to the position on Nation Grid.
There is also an explanation of the 3D viewing process to generate the virtual
taxiway geometries on the HUD. The communication between the traffic
console and airplane is also discussed
Monocular vision based indoor simultaneous localisation and mapping for quadrotor platform
Get PDFAn autonomous robot acting in an unknown dynamic environment requires a detailed understanding
of its surroundings. This information is provided by mapping algorithms which are
necessary to build a sensory representation of the environment and the vehicle states. This aids
the robot to avoid collisions with complex obstacles and to localize in six degrees of freedom i.e.
x, y, z, roll, pitch and yaw angle. This process, wherein, a robot builds a sensory representation
of the environment while estimating its own position and orientation in relation to those sensory
landmarks, is known as Simultaneous Localisation and Mapping (SLAM).
A common method for gauging environments are laser scanners, which enable mobile robots to
scan objects in a non-contact way. The use of laser scanners for SLAM has been studied and
successfully implemented. In this project, sensor fusion combining laser scanning and real time
image processing is investigated. Hence, this project deals with the implementation of a Visual
SLAM algorithm followed by design and development of a quadrotor platform which is equipped
with a camera, low range laser scanner and an on-board PC for autonomous navigation and
mapping of unstructured indoor environments.
This report presents a thorough account of the work done within the scope of this project.
It presents a brief summary of related work done in the domain of vision based navigation
and mapping before presenting a real time monocular vision based SLAM algorithm. A C++
implementation of the visual slam algorithm based on the Extended Kalman Filter is described.
This is followed by the design and development of the quadrotor platform. First, the baseline
speci cations are described followed by component selection, dynamics modelling, simulation
and control. The autonomous navigation algorithm is presented along with the simulation
results which show its suitability to real time application in dynamic environments. Finally,
the complete system architecture along with
ight test results are described
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