Computer Vision Based Object Tracking for Multiple Robot Collaboration

In this research we will consider the case in which industrial robotic manipulators execute pick and place operations with dynamically moving objects. Objects are considered to move on a conveyor belt of the production line without being precisely positioned on it. This research will investigate how a simple color camera can be used for recognition using computer vision methods for background subtraction. The proposed algorithm detects objects located on the conveyor belt of a production line and plans the grasping process for the multiple manipulating robots. It uses methods such as Mixture of Gaussians, which appear to be suitable for application in industrial environments. The algorithm was experimentally tested in a simulation environment. This leads to a universal approach, which does not require usage of special tools and sensors for the production line. The approach could be applied for each conveyor belt of any industrial production line. The grasp planning can consider a larger number of robots and optimize the sequence of their movements.