The SARAFun project is formed to enable a non-expert user to integrate a new bi-manual assembly task on a 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.

Over the last 30 years, robots have brought remarkable efficiency gains to industrial manufacturers, mainly in the automotive industry. Traditional industrial robots perform their assignments in cages and are heavily dependent on hard automation that requires pre-specified fixtures and time-consuming programming and reprogramming performed by experienced software engineers. The assembly application has always been considered as a promising robotic application but in reality it has proven challenging to automate due to e.g., complex materials, precise grasping requirements, part variations, operations requiring high precision (snap fits), operations requiring special motions (twist insertions) and wear and tear of the assembly equipment. While robotic assembly does exist, it has only been applied in a fraction of the potential cases. As a result, nowadays even expensive products produced in fairly large volumes, are still assembled manually in low wage countries under harsh conditions.

There is also a clear trend towards a shorter product lifetime. In order to be able to handle “burst” production (i.e. ramp up to full volume in very short time, run production for 3-12 months, and then change to new model) the lead time for setting up a production line/cell must be drastically reduced.

During the project, a system is developed that allows non-skilled users to teach a new bi-manual task to a robot in  less than a day. Following is a demo of the SARAFun system used in real industrial applications.


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