Passive Localization of a Robot Using Multiple-View Geometry

Passive Localization of a Robot Using Multiple-View Geometry

Ehsan Khoramshahi, Eija Honkavaara, Juha Hyyppä, Petri Myllymäki
Copyright: © 2014 |Pages: 17
DOI: 10.4018/IJRAT.2014070102
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Abstract

Finding the location of a robot, equipped with an imaging sensor, by taking photos from its surrounding environment is a multifaceted task consisting several obligatory phases. It starts from the calibration of a sensor, and ends in propagation of errors, to consequently express our uncertainty about the unknowns. This article uses a mathematical language to elaborate a model based on recent trends to show how the structure and motion can be estimated by image-processing methods on digital images taken from a regular non-metric camera. The direct and inverse Brown's model for calibration, as well as the basic definition of an image pyramid is discussed first. The concepts of Epipolar geometry, collinearity and co-planarity, and registrations of models, are described next. Generating a reference map, the bundle-adjustment and localization are presented finally. In the last sections, some recent trends about parallel computing are reviewed, and recommendations for building a real-time system are discussed.
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2. Camera

The most abstract element in a localization system is a regular camera, which is a light-measurement device. Two general types of regular camera exist in the market: the analogues and digitals. It is not so far that the analogues had a major rule in mapping; however, digital cameras are the main focus of this paper. A digital camera consists of a regular grid of sensors that measures the amount of light. A camera also contains an optical system that allows the light to be systematically measured by its sensors, and a linear or a set of linear arrays of sensors. In its most ideal form, the optical system consists of a single aperture that called the focal point. Each ray of light, after passing through this point, will put a signature on the front wall called image plane. Consequently the image formed by this setting is a mirror of the reality. Figure 1 demonstrates the setting of an ideal pinhole camera.

Figure 1.

Representation of an ideal (pinhole) camera

IJRAT.2014070102.f01

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