Intelligent Pose Control of Mobile Robots Using an Uncalibrated Eye-in-Hand Vision System

The use of material transfer units constructed from AGVs and robot manipulators is becoming popular in production lines with small production volumes and periods. This new material transfer unit is also called a mobile robot, which can quickly adapt to the change of the factory loyout. A mobile robot is sufficiently mobile that it can very flexibly perform tasks in the production line. A guidance control system drives a mobile base with a robot manipulator mounted on it to a predefined station so the robot manipulator can pick up a workpiece in the station. During pick-and-place operations, the relative location between a predefined station and the robot manipulator cannot be anticipated due to the possibility of the non-planar ground and/or the positioning errors caused by the guidance control system of the mobile base. Uncertainties in either the location of the mobile base or the level of ground flatness are responsible for a position mismatch, which normally causes failure in the pick-and-place operation. A more direct way of dealing with this problem is to use a CCD camera to provide visual feedback. The camera is typically mounted on the end-effector of the robot manipulator to compensate for these uncertainties using a visual servoing scheme. Hutchinson et al., 1996 classified the visual feedback control systems into four main categories. Position-based control aims to eliminate the errors determined by the pose of the target with respect to the camera; the features extracted from the image planes are used to estimate the pose in space. The control law then sends the command to the joint-level controllers to drive the servomechanism. This control architecture is the so-called hierarchical control and is referred to as the dynamic position-based look-and-move control structure. The control architecture is referred to as the position-based visual servo control structure if the servomechanism is directly controlled by the control law mentioned above rather than by the joint-level controller. The errors to the control law in image-based control, are directly governed by the extracted features of the image planes. The control architecture is hierarchical and referred to as the dynamic image-based look-and-move control structure if the errors are then sent to the joint-level controller to drive the servomechanism. The visual servo controller eliminates the joint-level controller and directly controls the servomechanism. Such control architecture is termed an image-based visual servo control structure.