A Visual Navigation Strategy Based on Inverse Perspective Transformation

Bonin‐Font, Francisco; Ortiz, Alberto; Oliver, Gabriel

doi:10.5772/9309

Cited by 3 publications

(3 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…All frames were undistorted to correct the error in the image point position due to the distortion introduced by the lens. For a varied set of scenes differing in light conditions and/or floor texture, the optimum β had a coincident value of 20mm [2]. The window used to find edge pixels near an obstacle point and to track down the obstacle contours is longer in the vertical direction to overcome possible discontinuities in the obstacle vertical borders.…”

Section: Resultsmentioning

confidence: 99%

“…More specifically, once a feature is matched between two frames, we assume it lies on the floor and we backproject the corresponding image points: the resulting world coordinates from both frames must coincide when the hypothesis is true, but they must be different when the feature comes from an elevated scene point. A threshold (β) can be defined as the maximum difference admissible between the backprojections on the floor [2].…”

Section: Inverse Perspective Transformation Feature Detection and Fementioning

confidence: 99%

See 1 more Smart Citation

Building a qualitative local occupancy grid in a new vision-based reactive navigation strategy for mobile robots

Bonin‐Font

Ortiz

2009

2009 IEEE Conference on Emerging Technologies &Amp; Factory Automation

Self Cite

View full text Add to dashboard Cite

Reactive navigation strategies for mobile robots base their success on the ability to discriminate obstacles from the ground in the vicinity of the robot and many of these strategies are based uniquely on the computation of quantitative information. In this paper we describe a new method to build qualitative local occupancy grids that are used in a new vision-based navigation strategy addressed to mobile robots to explore safely unknown environments. The process includes a new feature classifier based on the Inverse Perspective Transformation to discriminate object from ground points and a method to determine angle and range with respect to the camera in the world coordinate system.

show abstract

Section: Resultsmentioning

confidence: 99%

Section: Inverse Perspective Transformation Feature Detection and Fementioning

confidence: 99%

Building a qualitative local occupancy grid in a new vision-based reactive navigation strategy for mobile robots

Bonin‐Font

Ortiz

2009

2009 IEEE Conference on Emerging Technologies &Amp; Factory Automation

Self Cite

View full text Add to dashboard Cite

show abstract

“…[2] и Ortiz в 2010 г. [3]. Положим 1) I = (u, v) ∈ E 2 -плоское изображение в 2D пространстве; 2) W = (x, y, z) ∈ E 3 -3D изображение реальной дорожной сцены.…”

unclassified

Integration of the Light-Location and Television Data in Road Extraction Problems

Носков¹,

Ханин²

2012

EJSI

View full text Add to dashboard Cite

Рассмотрена актуальная задача навигации автономных роботизированных транспортных средств и мобильных роботов. Предложен подход к решению задачи поиска и распознавания дороги методом комплексирования данных лазерного сканера и системы видеокамер. Описаны устройство и алгоритмическое обеспечение системы технического зрения. Приведены результаты тестовых испытаний предложенного подхода.

show abstract

Mobile Robot Navigation Techniques Using Potential Field Method in Unknown Environments

Dumitru

Vlădăreanu

Yan

et al. 2014

AMM

View full text Add to dashboard Cite

In this paper, a navigation system for autonomous mobile robots that move into unknown environments based on artificial potential field is presented. The robot moves to a predefined target point while detects and maps every encounter object using its artificial monocular vision system based on intrinsic camera parameters. During navigation, every obstacle is associated with a repulsive field depending on the distance and relative position to the robot, while the target point has an attractive field. Combining those values of potential field defines the direction of the next step of the robot. The results reported are showing the behavior of the method in three scenarios, avoiding obstacles, going through a narrow corridor and escaping from a minimum local trap.

show abstract

A Visual Navigation Strategy Based on Inverse Perspective Transformation

Cited by 3 publications

References 25 publications

Building a qualitative local occupancy grid in a new vision-based reactive navigation strategy for mobile robots

Building a qualitative local occupancy grid in a new vision-based reactive navigation strategy for mobile robots

Integration of the Light-Location and Television Data in Road Extraction Problems

Mobile Robot Navigation Techniques Using Potential Field Method in Unknown Environments

Contact Info

Product

Resources

About