Intuitive Robot Programming by Capturing Human Manufacturing Skills: A Framework for the Process of Glass Adhesive Application

• Autor(a) principal: Babcinschi, Mihail
• Data de Publicação: 2023
• Outros Autores: Cruz, Francisco, Duarte, Nicole, Santos, Silvia, Alves, Samuel, Neto, Pedro
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
• Texto Completo: https://hdl.handle.net/10316/114665; https://doi.org/10.1007/978-3-031-17629-6_71
• topic: Robotics; Manufacturing Skills; Human-Robot Interfaces

There is a great demand for the robotization of manufacturing pro-cesses featuring monotonous labor. Some manufacturing tasks requiring specific skills (welding, painting, etc.) suffer from a lack of workers. Robots have been used in these tasks, but their flexibility is limited since they are still difficult to program/re-program by non-experts, making them inaccessible to most compa-nies. Robot offline programming (OLP) is reliable. However, generated paths directly from CAD/CAM do not include relevant parameters representing human skills such as robot end-effector orientations and velocities. This paper presents an intuitive robot programming system to capture human manufacturing skills and transform them into robot programs. Demonstrations from human skilled workers are recorded using a magnetic tracking system attached to the worker tools. Collected data include the orientations and velocity of the working paths. Positional data are extracted from CAD/CAM since its error when captured by the magnetic tracker, is significant. Paths poses are transformed in Cartesian space and validated in a simulation environment. Robot programs are generated and transferred to the real robot. Experiments on the process of glass adhesive application demonstrated the intuitiveness to use and effectiveness of the pro-posed framework in capturing human skills and transferring them to the robot.