Camera-Based Tracking of Floating Objects using Fixed-wing UAVs

Helgesen, Håkon Hagen; Bryne, Torleiv H.; Wilthil, Erik F.; Johansen, Tor Arne

doi:10.1007/s10846-021-01432-z

Cited by 10 publications

(7 citation statements)

References 30 publications

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“…According to the UAV's intended application, we can change the used payload (e.g., RGB or Infrared Radiation (IR) cameras) to be able to perform the mission. One of the most-common UAV applications is surveillance, where we can also automatically track the detected frame objects [73][74][75]. We can also use data fusion techniques to perform Simultaneous Localization And Mapping (SLAM) [76,77], which can also be used for autonomous landing in unknown environments [78].…”

Section: Uav Trackingmentioning

confidence: 99%

Fixed-Wing Unmanned Aerial Vehicle 3D-Model-Based Tracking for Autonomous Landing

Santos

Lobo

Bernardino

2023

Drones

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The vast increase in the available computational capability has allowed the application of Particle-Filter (PF)-based approaches for monocular 3D-model-based tracking. These filters depend on the computation of a likelihood function that is usually unavailable and can be approximated using a similarity metric. We can use temporal filtering techniques between filter iterations to achieve better results when dealing with this suboptimal approximation, which is particularly important when dealing with the Unmanned Aerial Vehicle (UAV) model symmetry. The similarity metric evaluation time is another critical concern since we usually want a real-time implementation. We explored, tested, and compared with the same dataset two different types of PFs, (i) an Unscented Bingham Filter (UBiF) and (ii) an Unscented Bingham–Gauss Filter (UBiGaF), using pose optimization in both implementations. Using optimization steps between iterations increases the convergence capability of the filter and decreases the obtained error. A new tree-based similarity metric approach is also explored based on the Distance Transform (DT), allowing a faster evaluation of the possibilities without losing accuracy. The results showed that the obtained pose estimation error is compatible with the automatic landing requirements.

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Section: Uav Trackingmentioning

confidence: 99%

Fixed-Wing Unmanned Aerial Vehicle 3D-Model-Based Tracking for Autonomous Landing

Santos

Lobo

Bernardino

2023

Drones

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“…Very often, in the literature, all the calculations demonstrated before are resumed in an unique Equation [4,[12][13][14], in the form:…”

Section: Camera Matrixmentioning

confidence: 99%

“…These acquisition devices can be RGB, infrared or hyperspectral cameras, for example. There are a variety of applications using such sensors, e.g., in the fields of inspection [1], mapping [2], search and rescue [3], tracking [4], border patrol [5], sea surveillance [6], agriculture [7], and even recreation [8].…”

Section: Introductionmentioning

confidence: 99%

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Comprehensive Direct Georeferencing of Aerial Images for Unmanned Aerial Systems Applications

Correia

Andrade

Sivertsen

et al. 2022

Sensors

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Optical image sensors are the most common remote sensing data acquisition devices present in Unmanned Aerial Systems (UAS). In this context, assigning a location in a geographic frame of reference to the acquired image is a necessary task in the majority of the applications. This process is denominated direct georeferencing when ground control points are not used. Despite it applies simple mathematical fundamentals, the complete direct georeferencing process involves much information, such as camera sensor characteristics, mounting measurements, attitude and position of the UAS, among others. In addition, there are many rotations and translations between the different reference frames, among many other details, which makes the whole process a considerable complex operation. Another problem is that manufacturers and software tools may use different reference frames posing additional difficulty when implementing the direct georeferencing. As this information is spread among many sources, researchers may face difficulties on having a complete vision of the method. In fact, there is absolutely no paper in the literature that explain this process in a comprehensive way. In order to supply this implicit demand, this paper presents a comprehensive method for direct georeferencing of aerial images acquired by cameras mounted on UAS, where all required information, mathematical operations and implementation steps are explained in detail. Finally, in order to show the practical use of the method and to prove its accuracy, both simulated and real flights were performed, where objects of the acquired images were georeferenced.

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“…Some particularly suitable areas of application of the proposed framework can be identified. High seas search and rescue missions are a good example [ 28 , 29 , 30 ], where people and/or small boats adrift at sea after shipwrecks or other disasters need to be tracked as closely and continuously as possible, in order to assess the prioritization strategy for rescue teams. Another example is surveillance missions involving suspicious vessels [ 31 ].…”

Section: State-of-the-art and The Main Contributionsmentioning

confidence: 99%

Flying Chameleons: A New Concept for Minimum-Deployment, Multiple-Target Tracking Drones

Vargas

Vivas

Rubio

et al. 2022

Sensors

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In this paper, we aim to open up new perspectives in the field of autonomous aerial surveillance and target tracking systems, by exploring an alternative that, surprisingly, and to the best of the authors’ knowledge, has not been addressed in that context by the research community thus far. It can be summarized by the following two questions. Under the scope of such applications, what are the implications and possibilities offered by mounting several steerable cameras onboard of each aerial agent? Second, how can optimization algorithms benefit from this new framework, in their attempt to provide more efficient and cost-effective solutions on these areas? The paper presents the idea as an additional degree of freedom to be exploited, which can enable more efficient alternatives in the deployment of such applications. As an initial approach, the problem of the optimal positioning with respect to a set of targets of one single agent, equipped with several onboard tracking cameras with different or variable focal lengths, is addressed. As a consequence of this allowed heterogeneity in focal lengths, the notion of distance needs to be adapted into a notion of optical range, as the agent can trade longer Euclidean distances for correspondingly longer focal lengths. Moreover, the proposed optimization indices try to balance, in an optimal way, the verticality of the viewpoints along with the optical range to the targets. Under these premises, several positioning strategies are proposed and comparatively evaluated.

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Camera-Based Tracking of Floating Objects using Fixed-wing UAVs

Cited by 10 publications

References 30 publications

Fixed-Wing Unmanned Aerial Vehicle 3D-Model-Based Tracking for Autonomous Landing

Fixed-Wing Unmanned Aerial Vehicle 3D-Model-Based Tracking for Autonomous Landing

Comprehensive Direct Georeferencing of Aerial Images for Unmanned Aerial Systems Applications

Flying Chameleons: A New Concept for Minimum-Deployment, Multiple-Target Tracking Drones

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