Abstract:
The integration of robotics and image processing has led to the realization of robot autonomy in dynamic
environments through the provision of visual feedback. This paper presents the application of parallel and open-link
robots in palletizing and shape drawing tasks as enhanced by visual feedback from image processing. In determining
the set of joint angles that could be used to reach the desired position and orientation of the end effector, the geometric
approach in which the spatial geometry of the robotic arms was decomposed into several plane geometry problems
was employed. Image processing techniques were used to enhance the performance of the robotic manipulators. In
one approach, Color-based segmentation was used to distinguish between different objects in the workspace by using
predefined color markers as references in the L*a*b color space. Classification of each pixel in the workspace image
was then done by calculating the Euclidean distance between that pixel and a predefined color marker. A second
approach employed Edge detection to identify the boundaries of objects within the workspace image by employing
the Hough Transform mathematical model to detect the abrupt changes in the image brightness pixel-wise. The pixel
locations from Hough were then sorted sequentially to outline the detected object. The integration of image
processing with the robotic tasks was expected to improve the precise detection of the position of objects as well as
the outline of geometric shapes. The incorporation of visual feedback allowed for dynamic robot manipulation in
which prior knowledge of the workspace was not requisite. This led to improved pick and place as well as shape
detection as applied in palletizing and shape drawing tasks actuated by the parallel and serial link manipulators,
respectively
