Abstract
This paper describes the system of video-data processing based on monocular vision for autonomous control of mobile robot. The system allows detecting obstacles in a robot environment modeled as a set of straight-line segment. The given system consists of three basic stages and uses original algorithms, ensuring the required precision and realization of the system in the real time. The first stage uses a fast edge detection algorithm on the basis of two- dimensional Walsh transform. The algorithm of modified Hough transform is used for detection of straight-line segments. The third stage «segment tracking» uses Kalman filtration for tracking segments in a monocular sequence of images.
Highlights
Traditional sensors for mobile robots can be divided into two broad categories: position sensors and visual sensors
Visual sensors can provide much richer and high-dimensional information about the environment, but only few vision processing schemes exist that can operate in real-time on a mobile platform in an unstructured environment [1,2]
Proposed video-processing scheme allows to increase the robustness of the system for mobile robot control
Summary
Traditional sensors for mobile robots can be divided into two broad categories: position sensors and visual sensors. The whole control system [7] consists of several neural networks and uses two independent informational streams to receive an information about environment: 1) video camera data, 2) data from ultrasonic sensors and infrared scanner. Walter′s ultrasonic sensors and infrared scanner are located in a single plane along the perimeter of the robot that allows receiving an information about distances to obstacles only in this plane. This robot is equipped by a single video camera covering approximately 55 deg. This robot is equipped by a single video camera covering approximately 55 deg. of visual field that forbids to use a stereo vision technique for an evaluation of distances to objects within the robot environment (fig. 2.)
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