Efficient Stereoscopic Video Matching and Map Reconstruction for a Wheeled Mobile Robot

Montiel, Oscar; Sepúlveda, Roberto; Castillo, Oscar; Quiñones, Jorge

doi:10.5772/50526

Cited by 5 publications

(7 citation statements)

References 22 publications

(26 reference statements)

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“…Stereo görüntülerde görüntü eşleştirme için birçok araştırmacı farklı yöntemler tercih etmektedir [25][26][27][28]. Stereo kameralı derinlik haritası çıkarımı ise görüntü içerisindeki nesnelerin birbirine göre durumlarını inceleyen, kısmi olarak mesafe bilgisi içeren çalışmalardır [27][28][29][30]. Stereo kameralı mesafe tespit sistemleri mobil araçlarda mesafe bilgisine erişmek için tercih edilen sistemler arasındadır [31,32].…”

Section: Discussionunclassified

Görüntü-Metre ile görüntü işleme tabanlı mesafe ölçümü

YANIK>¹,

Turan²

2022

Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi

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Günümüzde görüntü sensörleri (kameralar), görüntü analizi (sınıflandırma, segmentasyon vb.) ve sentezi (nesne tespit, takip, mesafe tespiti vb.) için yaygın olarak kullanılmaktadır. Çalışmada lazer-metre, lidar-metre, radar ve benzeri endüstriyel amaçlar için kullanılabilecek, görüntü işleme tabanlı bir ölçüm cihazının (Image-meter) geliştirilmesi için teorik temellerin atılması amaçlanmaktadır. Bu amaçla literatürdeki görüntü işleme tabanlı mesafe tespit yöntemleri incelenmiştir. Bu yöntemlerin başarımını olumsuz etkileyen temel etkenler tespit edilmiş, bu etkenlerden etkilenmeyen yeni bir yöntem geliştirilmiştir. Geliştirilmesi planlanan ölçüm cihazı teorik temellere oturtulmuştur. Bu teorik temellerin işletilmesi donanımsal ve yazılımsal bileşenlere dayandırılmıştır. Çalışmada bu teorik temeller verilmiş, donanımsal ve yazılımsal bileşenlerin tasarımları gerçekleştirilmiştir. 1-1000m için yapılan hesaplamalar sonucunda %0.2’nin altında başarı oranına ulaşılabileceği belirlenmiştir. Donanımsal ve yazılımsal bileşenlerin bu hata oranını artıracağı aşikardır. Bu hatalar standart ve random hatalardan oluşacaktır. Çalışmada bu hatalar öngörülmüş ve mesafe ölçüm denklemine ilave edilmiştir. Öngörülen hataların tespiti donanımsal prototipin ve yazılım bileşenlerin geliştirilmesi ile gelecek çalışmada belirlenecektir.

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Section: Discussionunclassified

Görüntü-Metre ile görüntü işleme tabanlı mesafe ölçümü

YANIK>¹,

Turan²

2022

Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi

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“…where Q is particle pairs which are included in an observation set, andij is the information of covariance matrix associated with an observation of particle j relative to particle i. The configuration of the particles x Ã minimizes the function (7) as follows…”

Section: Two-level Hierarchical Particle Invasion For Localization Anmentioning

confidence: 99%

“…Measure d dimensions of the similarity between two fingerprint sets, equations (7) and (8) the graph-pose scheme; key frames are used to decide whether the mobile robot is revisiting a place or not, that is, whether a loop is being closed. 4 For implementing a successful large-scale exploration, the mobile robot needs to base on building a topological map and maintaining the map consistency by using hierarchical metric -topological procedure and visual sensors.…”

Section: Programmentioning

confidence: 99%

“…gyrometers, odometer sensors, and inertial measurement unit (IMU)) in collapsed environments in which GPS is unavailable. O Montiel-Ross et al 7 guided a mobile robot using an adaptive candidate matching window instead of GPS data to accomplish an exploration through an environment with obstacles; there were four main processes (i.e. perception, localization, cognition, and motion control) involved in perception-driven exploration (PDE).…”

Section: Introductionmentioning

confidence: 99%

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A perception-driven exploration hierarchical simultaneous localization and mapping for mobile robots adapted to search and rescue environments

Wang

Zhang

Song

et al. 2018

Advances in Mechanical Engineering

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Perception-driven hierarchical simultaneous localization and mapping approach is proposed based on a distributed particle of percolator model adapted to search and rescue post-disaster environment. The proposed hierarchical analysis reduced the complexity; it can only highlight the interesting three-dimensional objects marked on the two-dimensional map, which adapted to urgent search and rescue post-disaster scenarios. Object identification, area coverage, and loop closure are the key issues that simultaneous localization and mapping faces when mobile robots detect and reach survivors in search and rescue collapsed environments. We developed hierarchical analysis using iterative extended Kalman filter method to improve the localization accuracy in simultaneous localization and mapping of mobile robots with an iteration process. An analytic hierarchical map-building mechanism efficiently constructs a globally consistent topological map using graph-based nodes and data association. An improved iterative extended Kalman filter procedure is used to estimate positions and the covariance matrix. The proposed algorithm incorporates a prediction step and a measurement update step, which performs the state vector time update in constant time interval and the correction of the state vector based on the new sensor measurement. The hierarchical mapping process is divided into three levels. The bottom level perceives the surroundings and collects input. The middle level receives and processes data from the bottom level. The upper level organizes the feature information from the previous levels to form a global, topologically consistent map. Simulations and experiments using the mobileRobot platform, Pioneer LX robot, and a crawler mobile robot validate the efficiency of this hierarchical simultaneous localization and mapping approach adapting to search and rescue post-disaster scenarios.

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“…Typically, the disparity is computed as a shift to the left of an image feature when it is viewed in the right image, it is calculated by determining a measure of the SAD, that is used to calculate disparities at each pixel in the right image [12]. After this SAD "match strength" has been computed for all valid disparities, the disparity that yields the lowest SAD is determined to be the disparity at that location in the right image.…”

Section: Introductionmentioning

confidence: 99%

Efficient determination of disparity map from stereo images with modified sum of absolute differences (SAD) algorithm

Hoa

Dung

Dzung

2013

2013 International Conference on Advanced Technologies for Communications (ATC 2013)

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This paper proposes modification of the conventional Sum of Absolute Differences (SAD) for performance improvement in depth-map estimation from stereo images captured by a camera in a stereo system. The conventional SAD is commonly search in whole stereo images to find out the difference in pixels between the left and right captured images, and then obtains the corresponding disparity map and this may lead to high elapsing time. In order to reduce the number of searching pixels, the proposed modified SAD tries to estimate the difference only from edge pixels which are referred as pixels-ofinterest and bring significant information about depth map. The number of pixels being searched is reduced to about 17% on the total pixels, hence the total elapsing time is saved up to around 89% compared to that of the conventional SAD. This results is promising for implementation of a real-time vision system. Keywords-sum of absolute difference, stereo camera, disparity map, stereo visionI.

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Efficient Stereoscopic Video Matching and Map Reconstruction for a Wheeled Mobile Robot

Cited by 5 publications

References 22 publications

Görüntü-Metre ile görüntü işleme tabanlı mesafe ölçümü

Görüntü-Metre ile görüntü işleme tabanlı mesafe ölçümü

A perception-driven exploration hierarchical simultaneous localization and mapping for mobile robots adapted to search and rescue environments

Efficient determination of disparity map from stereo images with modified sum of absolute differences (SAD) algorithm

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