Visual Odometry and Mapping for Autonomous Flight Using an RGB-D Camera

Huang, Albert S.; Bachrach, Abraham; Henry, Peter; Krainin, Michael; Maturana, Daniel; Fox, Dieter; Roy, Nicholas

doi:10.1007/978-3-319-29363-9_14

Cited by 386 publications

(292 citation statements)

References 25 publications

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“…The robotics community has focused on visual odometry approaches [20] and simultaneous and location mapping (SLAM) [21,22], while other groups related to geomatics and graphics are investigating semantic features [23] or structure from motion.…”

Section: State Of the Artmentioning

confidence: 99%

An Original Application of Image Recognition Based Location in Complex Indoor Environments

Chiabrando

Pietra

Lingua

et al. 2017

IJGI

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This paper describes the first results of an image recognition based location (IRBL) for a mobile application focusing on the procedure to generate a database of range images (RGB-D). In an indoor environment, to estimate the camera position and orientation, a prior spatial knowledge of the surroundings is needed. To achieve this objective, a complete 3D survey of two different environments (Bangbae metro station of Seoul and the Electronic and Telecommunications Research Institute (ETRI) building in Daejeon, Republic of Korea) was performed using a LiDAR (Light Detection and Ranging) instrument, and the obtained scans were processed to obtain a spatial model of the environments. From this, two databases of reference images were generated using specific software realised by the Geomatics group of Politecnico di Torino (ScanToRGBDImage). This tool allows us to generate synthetically different RGB-D images centred in each scan position in the environment. Later, the external parameters (X, Y, Z, ω, ϕ, and κ) and the range information extracted from the retrieved database images are used as reference information for pose estimation of a set of acquired mobile pictures in the IRBL procedure. In this paper, the survey operations, the approach for generating the RGB-D images, and the IRB strategy are reported. Finally, the analysis of the results and the validation test are described.

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Section: State Of the Artmentioning

confidence: 99%

An Original Application of Image Recognition Based Location in Complex Indoor Environments

Chiabrando

Pietra

Lingua

et al. 2017

IJGI

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“…There are visual odometry approaches [19], simultaneous and location mapping (SLAM) [24], structure from motion, or investigating semantic features [29]. Some interesting work exploits the computer vision algorithm and in particular the neural network and transfer learning for visual indoor positioning and classification [35].…”

Section: Cameras + Insmentioning

confidence: 99%

Positioning Techniques with Smartphone Technology: Performances and Methodologies in Outdoor and Indoor Scenarios

Dabove¹,

Pietra²,

Lingua³

2017

Smartphones From an Applied Research Perspective

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Smartphone technology is widespread both in the academy and in the commercial world. Almost every people have today a smartphone in their pocket, that are not only used to call other people but also to share their location on social networks or to plan activities. Today with a smartphone we can compute our position using the sensors settled inside the device that may also include accelerometers, gyroscopes and magnetometers, teslameter, proximity sensors, barometer, and GPS/GNSS chipset. In this chapter we want to analyze the state-of-the-art of the positioning with smartphone technology, considering both outdoor and indoor scenarios. Particular attention will be paid to this last situation, where the accuracy can be improved fusing information coming from more than one sensor. In particular, we will investigate an innovative method of image recognition based (IRB) technology, particularly useful in GNSS denied environment, taking into account the two main problems that arise when the IRB positioning methods are considered: the first one is the optimization of the battery, that implies the minimization of the frame rate, and secondly the latencies due to image processing for visual search solutions, required by the size of the database with the 3D environment images.

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“…In the robotics community, while depth cameras are being used for indoor mapping applications frequently in the recent years (Henry et al, 2010;Endres et al, 2012;Kerl et al, 2013), there is also a variety of research projects testing SLAM techniques for UAV equipped with laser scanners (Zhang and Singh, 2014) or depth cameras (Bachrach et al, 2014;Loianno et al, 2015;Karrer et al, 2016;Huang et al, 2017). On the other hand, although depth cameras have been tested for their performance in cultural heritage applications (Wenzel et al, 2012;Cappelletto et al, 2016), up to our knowledge, there is no much published work on using depth cameras mounted on UAV for cultural heritage applications.…”

Section: Related Workmentioning

confidence: 99%

DEPTH CAMERAS ON UAVs: A FIRST APPROACH

Deris¹,

Trigonis²,

Aravanis³

et al. 2017

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

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ABSTRACT:Accurate depth information retrieval of a scene is a field under investigation in the research areas of photogrammetry, computer vision and robotics. Various technologies, active, as well as passive, are used to serve this purpose such as laser scanning, photogrammetry and depth sensors, with the latter being a promising innovative approach for fast and accurate 3D object reconstruction using a broad variety of measuring principles including stereo vision, infrared light or laser beams. In this study we investigate the use of the newly designed Stereolab's ZED depth camera based on passive stereo depth calculation, mounted on an Unmanned Aerial Vehicle with an ad-hoc setup, specially designed for outdoor scene applications. Towards this direction, the results of its depth calculations and scene reconstruction generated by Simultaneous Localization and Mapping (SLAM) algorithms are compared and evaluated based on qualitative and quantitative criteria with respect to the ones derived by a typical Structure from Motion (SfM) and Multiple View Stereo (MVS) pipeline for a challenging cultural heritage application.

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Visual Odometry and Mapping for Autonomous Flight Using an RGB-D Camera

Cited by 386 publications

References 25 publications

An Original Application of Image Recognition Based Location in Complex Indoor Environments

An Original Application of Image Recognition Based Location in Complex Indoor Environments

Positioning Techniques with Smartphone Technology: Performances and Methodologies in Outdoor and Indoor Scenarios

DEPTH CAMERAS ON UAVs: A FIRST APPROACH

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