Smart Assembly Robots with Advanced Functionalities

Period: 2015-2018

The research leading to these results has received funding from the European Community’s Framework Programme Horizon 2020 – under grant agreement No 644938 – SARAFun.

The SARAFun project has been formed to enable a non-expert user to integrate a new bi-manual assembly task on a collaborative robot in less than a day. This will be accomplished by augmenting the robot with cutting edge sensory and cognitive abilities as well as reasoning abilities required to plan and execute an assembly task. The overall conceptual approach is that the robot should be capable of learning and executing assembly tasks in a human-like manner. Studies will be made to understand how human assembly workers learn and perform assembly tasks. The human performance will be modeled and transferred to the collaborative robot as assembly skills. The robot will learn assembly tasks, such as insertion or folding, by observing the task being performed by a human instructor. The robot will then analyze the task and generate an assembly program, including exception handling, and design 3D printable fingers tailored for gripping the parts at hand. Aided by the human instructor, the robot will finally learn to perform the actual assembly task, relying on sensory feedback from machine vision, force and tactile sensing as well as physical human robot interaction. During this phase the robot will gradually improve its understanding of the assembly at hand until it is capable of performing the assembly in a fast and robust manner.

Robotics Laboratory at Lund University contributes to SARAFun with task representation and learning of action sequences, contact graph formation and refinement via teaching assembly forces, sensorless contact force estimation, and evaluation of contacts for assembly.

Project staff

• Fredrik Bagge Carlson
• Mathias Haage
• Rolf Johansson
• Martin Karlsson
• Jacek Malec
• Klas Nilsson
• Anders Robertsson
• Maj Stenmark
• Elin A. Topp

Contact
Rolf Johansson
Rolf.Johansson@control.lth.se