UBRISTES: UAV-Based Building Rehabilitation with Visible and Thermal Infrared Remote Sensing

Carrio, Adrian; Pestana, Jesús; Sánchez-López, José Luis; Suarez-Fernandez, Ramon; Campoy, Pascual; Tendero, Ricardo; García-De-Viedma, María; González-Rodrigo, Beatriz; Bonatti, Javier; Ayuga, Juan Gregorio Rejas; Marín, Rubén Martínez; Marchamalo, Miguel

doi:10.1007/978-3-319-27146-0_19

Cited by 18 publications

(14 citation statements)

References 17 publications

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“…The bias terms are denoted by for the visible units and for the hidden units. The probability of a joint configuration over both visible and hidden units depends on the energy of that joint configuration and is given by (10), where ( ) represents the partition function (see (11)):…”

Section: Unsupervised Learningmentioning

confidence: 99%

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A Review of Deep Learning Methods and Applications for Unmanned Aerial Vehicles

et al. 2017

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Deep learning is recently showing outstanding results for solving a wide variety of robotic tasks in the areas of perception, planning, localization, and control. Its excellent capabilities for learning representations from the complex data acquired in real environments make it extremely suitable for many kinds of autonomous robotic applications. In parallel, Unmanned Aerial Vehicles (UAVs) are currently being extensively applied for several types of civilian tasks in applications going from security, surveillance, and disaster rescue to parcel delivery or warehouse management. In this paper, a thorough review has been performed on recent reported uses and applications of deep learning for UAVs, including the most relevant developments as well as their performances and limitations. In addition, a detailed explanation of the main deep learning techniques is provided. We conclude with a description of the main challenges for the application of deep learning for UAV-based solutions.

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Section: Unsupervised Learningmentioning

confidence: 99%

“…Some examples include power line inspection [9], wildlife conservation [10], building inspection [11], and precision agriculture [12]. However, UAVs have limitations in the size, weight, and power consumption of the payload and limited range and endurance.…”

Section: Introductionmentioning

confidence: 99%

A Review of Deep Learning Methods and Applications for Unmanned Aerial Vehicles

et al. 2017

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“…Multiple studies, [57], foresee a great number of civilian applications of multirotor aerial robots (also called drones or Unmanned Aerial Vehicles, UAVs), such as their integration in smart cities [40], or aerial inspection [9], among others. Most of these applications are either under research and development as prototypes or they are still simply concepts.…”

Section: Motivationmentioning

confidence: 99%

Trajectory Tracking for Aerial Robots: an Optimization-Based Planning and Control Approach

Sánchez-López

Castillo-Lopez

Olivares-Méndez

et al. 2020

J Intell Robot Syst

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In this work, we present an optimizationbased trajectory tracking solution for multirotor aerial robots given a geometrically feasible path.A trajectory planner generates a minimum-time kinematically and dynamically feasible trajectory that includes not only standard restrictions such as continuity and limits on the trajectory, constraints in the waypoints, and maximum distance between the planned trajectory and the given path, but also restrictions in the actuators of the aerial robot based on its dynamic model, guaranteeing that the planned trajectory is achievable. Our novel compact multi-phase trajectory definition, as a set of two different kinds of polynomials, provides a higher semantic encoding of the trajectory, which allows calculating an optimal solution but following a predefined simple profile.

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“…Hence, when the desire is to capture images for a whole building, one needs to assemble and disassemble the stationary system several times while moving around. So far, the utilization of a UAV for acquisition of such data sets are not well established, * Corresponding author but is starting to become an alternative approach (Carrio et al, 2016). A UAV multimodal system, in comparison to a stationary multimodal system, can acquire data at a faster pace and at higher altitudes.…”

Section: Introductionmentioning

confidence: 99%

Concept for Classifying Facade Elements Based on Material, Geometry and Thermal Radiation Using Multimodal Uav Remote Sensing

Ilehag

Schenk

Hinz

2017

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:This paper presents a concept for classification of facade elements, based on the material and the geometry of the elements in addition to the thermal radiation of the facade with the usage of a multimodal Unmanned Aerial Vehicle (UAV) system. Once the concept is finalized and functional, the workflow can be used for energy demand estimations for buildings by exploiting existing methods for estimation of heat transfer coefficient and the transmitted heat loss. The multimodal system consists of a thermal, a hyperspectral and an optical sensor, which can be operational with a UAV. While dealing with sensors that operate in different spectra and have different technical specifications, such as the radiometric and the geometric resolution, the challenges that are faced are presented. Addressed are the different approaches of data fusion, such as image registration, generation of 3D models by performing image matching and the means for classification based on either the geometry of the object or the pixel values. As a first step towards realizing the concept, the result from a geometric calibration with a designed multimodal calibration pattern is presented.

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UBRISTES: UAV-Based Building Rehabilitation with Visible and Thermal Infrared Remote Sensing

Cited by 18 publications

References 17 publications

A Review of Deep Learning Methods and Applications for Unmanned Aerial Vehicles

A Review of Deep Learning Methods and Applications for Unmanned Aerial Vehicles

Trajectory Tracking for Aerial Robots: an Optimization-Based Planning and Control Approach

Concept for Classifying Facade Elements Based on Material, Geometry and Thermal Radiation Using Multimodal Uav Remote Sensing

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