Princeton

Princeton is home to Siemens Technology’s North American Headquarters, the R&D hub where employees shape Siemens technology and innovation strategy. The company’s commitment to advance and secure its technology, including investing $1 billion in U.S. R&D annually, has resulted in 15,000 total U.S. patents, equating to five inventions per day. Siemens has nearly 2,100 employees in the state of New Jersey and over 250 in Princeton, where it has longstanding partnerships with Rutgers University and Princeton University.
A Resilient, Carbon-Neutral Campus

Defining the Future of Energy

Living lab provides leading-edge microgrid research environment for customers and partners.

The Siemens Advanced Microgrid Research and Demonstration Lab has been created at our Princeton campus to push the innovation envelope, to show what is possible in the realm of microgrids, and to research and demonstrate how various energy-related generation, storage and building management products behave and work together in a dynamic real-life microgrid environment. In addition, the facilities that support the living lab provide a co-creation space for public and private organizations looking to deploy highly integrated, sustainable and resilient microgrid solutions.

Can a robot learn new skills

So, will robots be able to change with the times to meet this new era of increasingly individualized consumer demand? Will robots be able to, as the saying goes, “Learn new skills”?

 

Researchers at Siemens believe the answer is a resounding yes.

AI-enhanced robotics and the future of manufacturing 

Two forms of artificial intelligence, Deep Learning and Reinforcement Learning (that can use Deep Learning), hold notable promise for solving such challenges because they enable robots in manufacturing systems to deal with uncertainties, to learn behaviors through interaction with their surrounding environments, and ideally generalize to new situations. Let’s take a look at how Deep Learning and Reinforcement Learning play a key role in the aforementioned use cases: flexible picking and the assembly of new components.