Robocoast R&D Demopaja: The Sign Language Robot
Satakunta hospital district issued Robocoast a new robotization challenge for a robot prototype that can repeat sign language. Robocoast also has to test the prototype functionality of the sign language robot in sign language lessons for children with autism. The hospital assumed that the robot could help children with autism to learn sign language easier using robots, but it should first be tested.
Robocoast first found out which existing robot platforms have two hands and five fingers whose function can be controlled as you want. Next, Robocoast chose the best possible experts to make the sign language robot prototype in the Robocoast R&D Demopaja workshop. Finally, a two-day test period was conducted, where the new robot prototype taught sign language to 12 children with autism. The results of the test were encouraging and development work for the sign language robot (MOMO Robot) will be continued by Futurice Ltd.
HYVÄKSI - Innovation Network on Welfare Technology
MatchINDUSTRY LAB: Case RoboCopper
As a part of the multinational Boliden Group, Boliden Harjavalta Ltd is specialized in smelting and refining copper in Satakunta region. In order to boost the production process of the Harjavalta smelter, Boliden launched the RoboCopper Challenge, with the aim to rethink the safety of the working conditions related to smelting furnaces. The smelting method used all over the world today was developed in the Harjavalta plant in 1949.
Robocoast challenged SMEs and their expert teams from the Robocoast cluster (consisting of round 100 automation, robotics and IoT companies and other actors) to create innovative cutting-edge solutions to improve the metallurgical processes.
In the Challenge, Hefmec Engineering innovated a game-changing solution to improve and simplify the 70-year old practices at Boliden’s smelter. After successful testing of the new solution it is possible for Hefmec Engineering to target international markets.
Robocoast utilized the expertise of the Robocoast cluster by using the Innovation Challenge model developed by Prizztech Ltd.
Robocoast R&D Center – Robotics And Automation Lab (SAMK): Recognizing Faulty Nails
A 1.5 ton vibration bowl feeder was brought to our RDI laboratory. It had been used for mechanical checking of nail straightness. There was a need to create a machine vision system to inspect the nails for straightness, excess scum and zinc coating.
3D printing was used to modify the existing system so that the nail could be imaged from every direction. A camera was installed so that it imaged the nails through diffuse dome light on the flat surface, and it could get around 10–15 images from each nail. This was enough for a 100% inspection.