[robotics-worldwide] [news] Siemens Robot Learning Challenge

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[robotics-worldwide] [news] Siemens Robot Learning Challenge

Solowjow, Eugen
Dear Robotics Community,

We kindly invite you to participate in the Siemens Robot Learning Challenge.

A dominant trend in manufacturing is the move toward small production volumes and high product variability. It is thus anticipated that future manufacturing automation systems will need to be able to learn new behaviors without explicit programming. Robot Learning covers the methodology, theory and art of enabling a robot, or any other automation system, to learn new skills and adapt to a flexible environment.

Researchers at Siemens Corporate Technology now provide a set of gears to benchmark different robot learning approaches. The assembly of these gears requires high precision and the ability to learn changing complex dynamics. How fast can your system learn? How much training data is required? What would you change in the design to make it even more challenging? These are all important questions that we want to open to the research community.

If you want to benchmark your robot learning algorithms and apply them to a challenging problem, 3D print the gears and share your results with us!

For more information, please visit
www.usa.siemens.com/robot-learning<https://urldefense.proofpoint.com/v2/url?u=http-3A__www.usa.siemens.com_robot-2Dlearning&d=DwIFAg&c=clK7kQUTWtAVEOVIgvi0NU5BOUHhpN0H8p7CSfnc_gI&r=0w3solp5fswiyWF2RL6rSs8MCeFamFEPafDTOhgTfYI&m=DmaKR5jflU8lR1ZzN3WQ0xaDuy86xG2wvU6f6FpoRnY&s=GRp30f2Ah9yagJe_754JhhdV-fJLzzLq8o9ooGlZol8&e=>

Contact: Juan Aparicio, Eugen Solowjow
Email: [hidden email]<mailto:[hidden email]>, [hidden email]<mailto:[hidden email]>

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