Compensation of SCARA Robot Positioning Error using Stereo Camera

Decidability of Robot Positioning Tasks Using Stereo Vision Systems

Conditions are given which enable one to decide on the basis of images of point features observed by an imprecisely modeled two-camera stereo vision system, whether or not a prescribed robot positioning task has been accomplished with precision. It is shown that for a stereo vision system whose two-camera model is known only up to a projective transformation, one can decide with the available d...

Machine tool positioning error compensation using artificial neural networks

This thesis is a study of the application of artificial neural networks to the problem of calculating error compensation values for axis positioning on a machine tool. The primary focus is on the development of a neural network-based system that could be implemented and integrated into the open architecture control system of an actual machine. A number of neural network architectures were exami...

Camera Calibration Error Analysis in Stereo Measurements

Camera calibration is an important and sensitive step in 3D environment reconstruction by stereovision. Small errors in the estimation of the camera parameters could rise to high errors in the 3D measurements, as the working distance increases. Therefore a method for analyzing the influence of each camera’s parameter error in the accuracy of the 3D measurement is compulsory in order to minimize...

Depth error compensation for camera fusion system

Obstacle Avoidance Using Stereo Camera

In this paper we present a novel method for obstacle avoidance using the stereo camera. The conventional obstacle avoidance methods and their limitations are discussed. A new algorithm is developed for the real-time obstacle avoidance which responds faster to unexpected obstacles. In this approach the depth map is divided into optimized number of regions and the minimum depth at each section is...