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Vision Based Position Control of a Robot Manipulator Using an Elitist Genetic Algorithm  

Park, Kwang-Ho (Dept.of Mechanical Engineering, Graduate School of Chonnam National Universityisy)
Kim, Dong-Joon (Dept.of Mechanical Engineering, Graduate School of Chonnam National Universityisy)
Kee, Seok-Ho (Dept. of Mechanical Eng., Seokang College)
Kee, Chang-Doo (Dept.of Mechanical Engineering, Chonnam National Universityisy)
Publication Information
Journal of the Korean Society for Precision Engineering / v.19, no.1, 2002 , pp. 119-126 More about this Journal
Abstract
In this paper, we present a new approach based on an elitist genetic algorithm for the task of aligning the position of a robot gripper using CCD cameras. The vision-based control scheme for the task of aligning the gripper with the desired position is implemented by image information. The relationship between the camera space location and the robot joint coordinates is estimated using a camera-space parameter modal that generalizes known manipulator kinematics to accommodate unknown relative camera position and orientation. To find the joint angles of a robot manipulator for reaching the target position in the image space, we apply an elitist genetic algorithm instead of a nonlinear least square error method. Since GA employs parallel search, it has good performance in solving optimization problems. In order to improve convergence speed, the real coding method and geometry constraint conditions are used. Experiments are carried out to exhibit the effectiveness of vision-based control using an elitist genetic algorithm with a real coding method.
Keywords
Elitist genetic algorithm; Vision based control; , Camera estimation method; Optimization; Image feature points;
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