Fast and Accurate Robot Vision for Vision Based Motion
نویسندگان
چکیده
This paper describes the vision module from the soccer playing robots of the Dutch Team. Fast vision is necessary to get a close coupling with the motion software in order to allow fast turning and dribbling with the ball without loosing it. Accurate vision is necessary for the determination of the robot's position in the field and the accurate estimation of the ball position. Both fast and accurate are necessary for the goalkeeper, but also when one robot passes the ball to another. While the Dutch team has pneumatic kicking devices that allows catching a ball smoothly, fast an accurate vision is mandatory. We use lens undistortion, a new color segmentation scheme and a shape classification scheme based on linear and circular Hough transforms in regions of Interest. We use a severe calibration procedure to get very good distance and angle measurements of the known objects in the field of view of the robot. For the keeper robot we use a Linear Processor Array in SIMD mode, that is able to execute the entire robust vision algorithm within 30ms. However the same software was programmed for the other robots with a WinTV framegrabber on the on-board Pentium of the robot. With optimizing for speed we also remained within 25ms, however, omitting the circular Hough transform for the ball and processing in a separate thread the Linear Hough transforms for self-localization on lower rate of about 50msec. The angular errors at 0 °, 20 ° and 30° heading are about 0.6 °, 0.0° and 0.4°. The distance error at 0 ° heading is 2cm at 1.5m and 3 cm at 2m.
منابع مشابه
Robot Motion Vision Part II: Implementation
The idea of Fixation introduced a direct method for general recovery of shape and motion from images without using either feature correspondence or optical flow [1,2]. There are some parameters which have important effects on the performance of fixation method. However, the theory of fixation does not say anything about the autonomous and correct choice of those parameters. This paper presents ...
متن کاملRobot Motion Vision Pait I: Theory
A direct method called fixation is introduced for solving the general motion vision problem, arbitrary motion relative to an arbitrary environment. This method results in a linear constraint equation which explicitly expresses the rotational velocity in terms of the translational velocity. The combination of this constraint equation with the Brightness-Change Constraint Equation solves the gene...
متن کاملParameters Identification of an Experimental Vision-based Target Tracker Robot Using Genetic Algorithm
In this paper, the uncertain dynamic parameters of an experimental target tracker robot are identified through the application of genetic algorithm. The considered serial robot is a two-degree-of-freedom dynamic system with two revolute joints in which damping coefficients and inertia terms are uncertain. First, dynamic equations governing the robot system are extracted and then, simulated nume...
متن کاملFast recognition based on color image segmentation in mobile robot
Real time segmentation is the first step in the color vision system on the robot system.A color image segmentation method using improved seed-fill algorithm in YUV color space is introduced in this paper. The new method dramatically reduces the work of calculation,and speeds up the image processing. The result of comparing it with the old method based on RGB color space was showed in the paper....
متن کاملComputation Optical Flow Using Pipeline Architecture
Accurate estimation of motion from time-varying imagery has been a popular problem in vision studies, This information can be used in segmentation, 3D motion and shape recovery, target tracking, and other problems in scene analysis and interpretation. We have presented a dynamic image model for estimating image motion from image sequences, and have shown how the solution can be obtained from a ...
متن کامل