The CircuBot project aims to develop several enabling technologies (targeted in specific objectives – SO) that could significantly improve the waste sorting process modularly or combined within the finally targeted solution:

Figure 1. The proposed concept for Deep learning based collaborative waste sorting.

Specific objective 1 (SO1) – To enable versatile visual waste detection and sorting. CircuBot will develop an artificial intelligence-based system for waste sorting. In collaboration with industry partners, we will enlarge publicly available datasets and develop novel algorithms for the recognition and sorting of waste objects with respect to their visual appearance, dimensions, color, mass, damage levels, and material characteristics (to name a few waste sorting criteria).

Specific objective 2 (SO2) – To enable cooperative human/robot waste picking: CircuBot will improve waste picking by optimizing: 1) robot grasping strategy for a typical class of objects, and 2) task sharing between humans and robots as cooperative agents in picking tasks in a safe and efficient manner. The SO2 will also include the evaluation of the success of catching with individual grippers for characteristic types of objects, as well as the analysis of the efficiency and safety of the work of the human operator, who collects individual types of waste on the conveyor belt.

Specific objective 3 (SO3) – To improve the efficiency of the waste handling process on the robotics side: We will develop a novel strategy for dynamic pick-and-toss manipulation of objects to make compliant robot’s sorting more time and energy efficient – while ensuring assisting a human operator in a safe manner. We will exploit the principal advantages of cutting-edge compliant robot technology: 1) soft end-effectors will be used for precise catching of various types of waste, 2) the capability of storing/releasing energy will be used for achieving efficient throwing strategies, 3) the inherent compliance within robot joints will be used for enabling safe physical human-robot collaboration.

Specific objective 4 (SO4) – To digitalize the waste sorting management: We will significantly reduce the load to top-management and waste experts (whose physical presence is currently necessary to monitor sorting processes) by developing a cloud management platform that will be integrated with the CircuBot workstation. By using IoT, Big Data and Cloud computing we will enable more objective and transparent decision-making through the use of Data mining and Machine learning for pattern analysis, forecasting, fault detection and trend estimation.

Figure 2. The proposed concept for collaborative waste sorting.