Скачать или смотреть R3M Project - Battery Disassembly Use-Case (Cranfield Uni ABB IRB-120 Cell)

The R3M Project is dedicated to advancing adaptable and responsive manufacturing systems by leveraging cutting-edge robotics, AI, and automation. A key challenge in modern manufacturing is the inefficiency and high cost associated with reprogramming robotic systems to handle varying product demands. The R3M approach tackles this issue by developing algorithms capable of automatically generating configuration and programming data from product and process requirements, equipment specifications and CAD inputs, significantly reducing manual intervention.

ROS 2 has been the primary enabler for the reconfigurability and adaptability of the R3M system. By utilizing its modular architecture, real-time performance, and scalability, we have developed an automation framework that allows robotic systems to be dynamically reconfigured based on production demands. Through ROS 2’s distributed communication mechanisms, robotic cells can seamlessly integrate with external software and hardware components, ensuring interoperability across different manufacturers and setups. This integration is key to reducing downtime, improving efficiency, and enabling flexible automation, all of which are core objectives of the R3M Project.

The R3M Project is an EPSRC-funded UK research initiative (EP/V051180/1) focused on Reconfigurable Robotics for Responsive Manufacture. Led by Cranfield University, it is a collaborative effort involving Loughborough University, the University of Sheffield, and AMRC-Sheffield. Together, these institutions are working to develop next-generation, adaptable manufacturing systems that can dynamically respond to changing production needs while improving efficiency and reducing costs.

(c) IFRA Research Group
Centre for Robotics and Assembly
Faculty of Engineering and Applied Sciences (FEAS)
Cranfield University
[email protected]

Credits -
Researcher: Mikel Bueno Viso ([email protected])
Supervisor: Dr. Seemal Asif ([email protected])
Supervisor: Prof. Phil Webb ([email protected])