HR-Recycler

The technical and technological advances that have been achieved over the past decades have led to a tremendous increase in both the types as well as the total amount of electrical and electronic equipment that is manufactured by the industry. On the other hand, the lowering of industrial production costs with the continuous and rapid change in technology has resulted in the widespread use of the produced devices in large quantities, along with the continuous need to often be upgraded or replaced. The above facts have led to the generation of enormous amounts of Waste Electrical and Electronic Equipment (WEEE). The importance of managing the WEEE materials and its tremendous impact on the economy, society, and environment is easy to be realized, by considering that the production of common electrical and electronic equipment (e.g. smartphones, PCs, monitors, tablets, home appliances, etc.) requires highly expensive and often rare material types (e.g. gold, copper, steel, etc.). Despite the great importance and the tremendous economic/environmental/societal impact of WEEE management, the current technology is still confronted with challenges, such as hazardous WEEE materials, human and environmental risks, illegal activities, recycling costs, and strict policies. Therefore, a ‘hybrid human-robot recycling plant for electrical and electronic equipment (HR-Recycler)’ operating in an indoor environment for the recycling of WEEE is desired. The ultimate goal of this project is to develop a sophisticated open human-robot working environment that will implement an HR-Recycler operating in an indoor setting. The fundamental principle behind the design of the envisaged system is the replacement of multiple currently manual, expensive, hazardous, and time-consuming tasks of WEEE materials pre-processing with correspondingly automatic robotic-based procedures, fused within a genuine human-robot collaboration context that will boost the productivity and quality of work in the plant. The primary output of the envisaged system will be to extract sorted electric/electronic device components and concentrated fractions of increased economic and environmental value; hence, contributing to the fundamental goal of the ‘European circular economy’ project and boosting economic activity in secondary markets.

Period: 2018.12 - 2021.11

Role: Participant as a doctoral candidate

Principal Investigator:  PD Dr.-Ing. habil. Dirk Wollherr

Affiliation: Technical University of Munich

Funding Source: European Union Commission

Website: https://www.hr-recycler.eu/

Consortium: Centre for Research and Technology Hellas (CERTH), Institute for Bioengineering of Catalonia (IBEC), Tecnalia Research & Innovation (Tecnalia), Vrije Universiteit Brussel (VUB), COMAU, Diginext, GAIKER Technology Centre, Sadako Technologies, Robotnik, Baianat, Interecycling, Indumental.

The main objectives of HR-Recycler include:

• Phase 1: define the use cases and scenarios, the elicit user requirements, the ethics/regulation/social acceptance and system requirements, model the dynamic assessment, and define the system architecture and the system integration plan.

• Phase 2: the first system validation in the lab with core developments of the robotic platform, the AI-enabled perception tools, the robot planning and control methods, human-robot collaboration schemes, and factory-level modeling and cognitive perception.

• Phase 3: based on the feedback from Phase 2, develop new prototypes, including complete functionality for all HR-Recycler services and tools, and evaluate the prototypes at both usability and performance levels. Lab testing will be exponentially increased, including initial user evaluation, the first version of the pilots, and the analysis and assessment of the usability and impact creation.

• Phase 4: based on the evaluation results of Phase 3, refine the final set of tools after the first validation stage in relevant environments by taking into account feedback and improvements required by end users. Conduct the second stage of pilots to achieve a complete demonstration in relevant environments.

Publications

• Y. Wang, Z. Zhang*, C. Li, and M. Buss, Adaptive incremental sliding mode control for a robot manipulator, in Mechatronics, vol. 82, no. 2022, pp. 102717, 2022, doi: 10.1016/j.mechatronics.2021.102717. [ScienceDirect]

• Z. Zhang, Y. Wang*, and Dirk Wollherr, "Safe Tracking Control of Euler-Lagrangian Systems Based on A Novel Adaptive Super-twisting Algorithm", in IFAC-PapersOnLine, vol. 53, no. 2, pp. 9974-9979, July. 2020, doi: 10.1016/j.ifacol.2020.12.2714. [ScienceDirect]

• Z. Zhang, K. Qian*, B. W. Schuller, and D. Wollherr, "An Online Robot Collision Detection and Identification Scheme by Supervised Learning and Bayesian Decision Theory," in IEEE Transactions on Automation Science and Engineering, vol. 18, no. 3, pp. 1144-1156, July. 2021, doi: 10.1109/TASE.2020.2997094. [IEEEXplore]