A low-cost stereoscopic µP-based vision system for industrial light objects grasping

This article describes a vision-based manipulation process for real-time moving objects tracking and grasping, aiming at industrial manufacturing and assembling applications. The adoption of computervision techniques for object recognition is implemented by means of a stereoscopic system using color based methods under OpenCV libraries.

The visual software is directly coupled with the control software of the robotic arm Katana 6M90G manufactured by Neuronics AG, running under a Linux-based Operating System (OS) distribution Lubuntu, over a low-cost and powerful microprocessor Odroid U3. Experimental studies validate the effectiveness of the implementation, while remarking the advantageous effects of the 3D pose estimation process.