A Method for Recognizing Object's ID and Detecting its Pose Under Varying Light Condition for Visual Feedback Control

Abstract

It is important to make its vision system more robust and accurate, to give optimal visual-feedback, which helps to control a robot. We propose a robust and accurate pattern matching method for simultaneously identifying robots and estimating their orientations that does not use color segmentation. To search for similar patterns, our approach uses continuous DP matching, which is obtained by scanning at an ellipse circumference from the center of the robot. The DP similarity value is used to identify object, and to obtain the optimal route by back tracing to estimate its orientation. We found that our system's ability to identify objects was robust to variation in light conditions. This is because it can take advantage of the changes in intensity only. [4]

Robust location tracking method for mixed reality robots using a rotation search method

“…Rotation search is a method for detecting images using template images rotated at certain angles [6], [7]. In the case of a detection failure, the correlation value of the relevant area becomes higher than that of other areas, even if the image of the marker is depleted due to changes in illuminance and motion blur.…”