ROS 2 for enhancing perception and recognition in collaborative robots performing flexible tasks

The advent of increasingly flexible and adaptive production processes will require equally flexible robotic collaboration. The forthcoming robotic applications must be able to self-adapt to different applications and scenarios and to handle frequent interaction with humans and dynamic environments. Environment perception, object recognition, and trajectory re-planning in a dynamic and changing environment, even with possible human interaction, are features that are not yet all simultaneously available in collaborative robots, and certainly not in industrial robots. This paper proposes some initial results of the authors’ ongoing research on the development of a ROS2-based framework for industrial applications due to which a robotic manipulator equipped with a depth camera is able to have simultaneously perception, recognition and re-planning capabilities in a dynamic and changing environment. This framework is potentially applicable to various industrial robots and depth cameras; here, the first results of the experimental implementation on an Omron TM5-900 collaborative robot equipped with a fixed depth camera will be shown.