3D Vision-Based Control on an Industrial Robot

Industrial robots are designed for tasks such as pick and place, welding, and painting. The environment and the working conditions for those tasks are well set. If the working conditions changed, those robots may not be able to work properly. Therefore, external sensors are necessary to enhance the robot’s capability to work in a dynamic environment. A vision sensor is an important sensor that can be used to extend the robot’s capabilities. The image of objects of interest can be extracted from their environment, and then information from these images can be computed to control the robot. The control that uses the images as feed back signals is known as vision based control. Recently, vision-based control has become a major research field in robotics.

Vision-based control can be classified into two main categories. The first approach, feature based visual control, uses image features of a target object from image (sensor) space to compute error signals directly. The error signals are then used to compute the required actuation signals for the robot. The control law is also expressed in the image space. Many researchers in this approach use a mapping function (Jacobian) from the image space to the Cartesian space.

The image Jacobian, generally, is a function of the focal length of the lens of the camera, depth, and the image features.

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