Staying ship-shape with drone swarms
How do you visually inspect an entire battleship quickly and safely? Send up the drones. A joint effort by the United States Navy, the Advanced Robotics for Manufacturing (ARM) Institute, and a team assembled from across Siemens USA and Allen Business Ventures (ABV) has demonstrated the ability to inspect large ships and structures using an autonomous drone swarm. This successful experiment has shown how autonomous drones can rapidly inspect large assets—for corrosion, damage, or stresses—and be used for creating the digital twin of such assets.
Research and Innovation Ecosystems: addressing today’s challenges with future technologies
The Siemens Research and Innovation Ecosystem (RIE) program—with four American Ecosystems and 12 globally—engages with researchers, employees, customers, founders, students, and innovative minds to address today’s challenges with future technologies. Siemens Technology, located in Princeton, NJ, Charlotte, NC and Berkeley, CA, has active research partnerships in the four Ecosystems in the U.S.: Atlanta, The Bay Area, Greater Boston, and the Industrial Midwest.
Defining the future of energy
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.