The ReconCycle project’s primary focus was to create a fully modular, adaptable robotic system for e-waste disassembly. Central to this was the development of a standardized module that serves as the building block for various specialized components, including robot modules using a torque-controlled manipulator, and a suite of soft grippers and fixtures such as the qb SoftHand 2, Variable Stiffness Gripper (VSG), and SoftClamp. The system also included functional units like cutter modules, CNC milling capabilities, and tool exchange mechanisms. The innovative Plug-and-Produce (PnP) connector allows for reliable, stable integration of different modules, providing mechanical stability, electrical and pneumatic power, and data connectivity. This feature enables rapid and seamless reconfiguration of the disassembly workcell.
The software architecture, based on the Robot Operating System (ROS), was designed to facilitate easy control and reconfiguration of the workcell, even for non-experts. Tools like the FlexBE behavior engine and simulation environments such as Rviz and Gazebo enable efficient programming, testing, and refinement of disassembly tasks. A key focus of the project was on the development of advanced tactile manipulation capabilities, using a unified force-impedance control strategy. This approach dynamically adjusts manipulation forces based on real-time sensory feedback. This way precise and safe handling of both fragile and rigid components during disassembly can be ensured.
Advanced AI techniques, including computer vision and neural networks, played a crucial role in guiding the robotic system. Object recognition, pose estimation, and scene analysis were enhanced by integrating the latest vision-language models (VLMs), which provide context-aware action prediction. This allows the system to interpret complex and varied structures of electronic devices, improving its ability to adapt dynamically to different disassembly tasks. The use of soft robotics, with sensorized end-effectors and adaptable tool exchange systems, expands the functional range of the workcell, enabling tasks like removing snap-fit parts without special components.
The developed workcell underwent extensive testing against predefined Key Performance Indicators (KPIs), demonstrating significant improvements in adaptability, efficiency, and safety. The project was able to meet most of its targets, proving the robustness and readiness of the system for industrial applications.
The consortium also made extensive dissemination efforts, with the project partners publishing numerous scientific papers, presenting at industrial fairs, and engaging with the broader research community through open-source software releases and collaborative events. Business and commercialization efforts identified several promising results, including the market potential of soft robotics solutions and modular PnP connectors, laying the groundwork for future industrial applications.
