Visual Target Tracking and Relative Navigation for Unmanned Aerial Vehicles in a GPS-Denied Environment

Kim, Youngjoo; Jung, Wooyoung; Bang, Hyochoong

doi:10.5139/ijass.2014.15.3.258

Cited by 18 publications

(12 citation statements)

References 6 publications

(9 reference statements)

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“…In Fig. 8 three target following examples are depicted as it follows: a) [113], b) [114], c) [115]. In this Figure downward looking cameras onboard aerial vehicle are used for target detection and tracking.…”

Section: Aerial Target Trackingmentioning

confidence: 99%

See 1 more Smart Citation

Survey on Computer Vision for UAVs: Current Developments and Trends

Kanellakis

Nikolakopoulos

2017

J Intell Robot Syst

289

120

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During last decade the scientific research on Unmanned Aerial Vehicless (UAVs) increased spectacularly and led to the design of multiple types of aerial platforms. The major challenge today is the development of autonomously operating aerial agents capable of completing missions independently of human interaction. To this extent, visual sensing techniques have been integrated in the control pipeline of the UAVs in order to enhance their navigation and guidance skills. The aim of this article is to present a comprehensive literature review on vision based applications for UAVs focusing mainly on current developments and trends. These applications are sorted in different categories according to the research topics among various research groups. More specifically vision based position-attitude control, pose estimation and mapping, obstacle detection as well as target tracking are the identified components towards autonomous agents. Aerial platforms could reach greater level of autonomy by integrating all these technologies onboard. Additionally, throughout this article the concept of fusion multiple sensors is highlighted, while an overview on the challenges C. Kanellakis ( ) · G. Nikolakopoulos Luleå University of Technology, Luleå, Sweden e-mail: christoforos.kanellakis@ltu.se G. Nikolakopoulos e-mail: geonik@ltu.se addressed and future trends in autonomous agent development will be also provided.

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Section: Aerial Target Trackingmentioning

confidence: 99%

“…In [113] an emergency Inertial-Vision navigation system dealing with GPS-denied environments has been proposed. Whenever a UAV was losing its GPS signal during the flight the designed navigation system performed real-time visual target tracking and relative navigation.…”

Section: Aerial Target Trackingmentioning

confidence: 99%

Survey on Computer Vision for UAVs: Current Developments and Trends

Kanellakis

Nikolakopoulos

2017

J Intell Robot Syst

289

120

View full text Add to dashboard Cite

show abstract

“…Illyas et al present a novel algorithm for micro-planetary rover-heading determination using a low-cost sun sensor, and a large number of experiments show that the heading precision reaches 0.09 ∘ (1 ), which plays an important role in reducing the accumulated heading error of MEMS sensors [9]. In a GPS-denied environment, visual navigation can provide accurate localization [10], but the error grows sharply with the distance travelled. Lambert et al develop a novel approach incorporating the sun sensor and inclinometer measurements directly into the visual odometry pipeline to reduce the error growth of path estimation, and the resulting localization error is only 1.1% of a 10-km distance travelled [11].…”

Section: Introductionmentioning

confidence: 99%

High-Precision Heading Determination Based on the Sun for Mars Rover

Yu¹,

Chen

2018

Advances in Astronomy

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Since the American Mars Exploration Rover Opportunity landed on Mars in 2004, it has travelled more than 40 km, and heading-determination technology based on its sun sensor has played an important role in safe driving of the rover. A high-precision heading-determination method will always play a significant role in the rover’s autonomous navigation system, and the precision of the measured heading strongly affects the navigation results. In order to improve the heading precision to the 1-arcminute level, this paper puts forward a novel calibration algorithm for solving the comparable distortion of large-field sun sensor by introducing an antisymmetric matrix. The sun sensor and inclinometer alignment model are then described in detail to maintain a high-precision horizon datum, and a strict sun image centroid-extraction algorithm combining subpixel edge detection with circle or ellipse fitting is presented. A prototype comprising a sun sensor, electronic inclinometer, and chip-scale atomic clock is developed for testing the algorithms, models, and methods presented in this paper. Three field tests were conducted in different months during 2017. The results show that the precision of the heading determination reaches 0.28–0.97′ (1σ) and the centroid error of the sun image and the sun elevation are major factors that affect the heading precision.

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“…However, in the case of a circular trajectory, the response time may be late because the follower has a transient response. The roll angle of the leader, which is obtained from an image, is fed (11) r the n the eneral, n be aterial curate e not a δ , and and r ) nction nverse deling. ut and tilized obtain ge of while .…”

Section: Uav System Modelingmentioning

confidence: 99%

“…This method has the shortcoming that the infrared LEDs must be attached at the wing tips, elevator, and vertical stabilizer [10]. Other similar studies about operating UAVs in a jamming environment have been carried out [11].…”

Section: Introductionmentioning

confidence: 99%

Monocular Vision-Based Guidance and Control for a Formation Flight

Cheon¹,

Kim

Min³

et al. 2015

International Journal of Aeronautical and Space Sciences

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This paper describes a monocular vision-based formation flight technology using two fixed wing unmanned aerial vehicles. To measuring relative position and attitude of a leader aircraft, a monocular camera installed in the front of the follower aircraft captures an image of the leader, and position and attitude are measured from the image using the KLT feature point tracker and POSIT algorithm. To verify the feasibility of this vision processing algorithm, a field test was performed using two light sports aircraft, and our experimental results show that the proposed monocular vision-based measurement algorithm is feasible. Performance verification for the proposed formation flight technology was carried out using the X-Plane flight simulator. The formation flight simulation system consists of two PCs playing the role of leader and follower. When the leader flies by the command of user, the follower aircraft tracks the leader by designed guidance and a PI control law, and all the information about leader was measured using monocular vision. This simulation shows that guidance using relative attitude information tracks the leader aircraft better than not using attitude information. This simulation shows absolute average errors for the relative position as follows: X-axis: 2.88 m, Y-axis: 2.09 m, and Z-axis: 0.44 m.

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Visual Target Tracking and Relative Navigation for Unmanned Aerial Vehicles in a GPS-Denied Environment

Cited by 18 publications

References 6 publications

Survey on Computer Vision for UAVs: Current Developments and Trends

Survey on Computer Vision for UAVs: Current Developments and Trends

High-Precision Heading Determination Based on the Sun for Mars Rover

Monocular Vision-Based Guidance and Control for a Formation Flight

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