Kraken Sets Up Subsidiary in Bremen

Kraken Sonar Inc. informed that effective January 1, 2017, its new German subsidiary, Kraken Robotik GmbH (KRG) will start operations at the Bremen Innovation and Technology Centre (BITZ).

In addition to customer support, KRG will focus on the development of 3D imaging sensors, machine learning and artificial intelligence (AI) algorithms for underwater robotic platforms. Machine learning is a type of AI that provides robots with the ability to learn without being explicitly programmed. Machine learning focuses on the development of software that can teach robotic platforms to be cognitive and adaptive when exposed to new data.

“We believe that underwater robotics technology has finally reached its tipping point,” said Karl Kenny, Kraken’s president & CEO. “Today’s underwater robotics industry can be compared to the digital photography industry; over the past 15 years we’ve gone from 35mm film to now having camera sensors on a chip and images in the cloud. Next generation underwater robotic platforms will also be sensor-centric to reduce costs and simplify their ease of use. The future of underwater robotics will be less about commodity hardware and more about innovative sensors using very smart algorithms and artificial intelligence. That’s the fundamental thinking that led us to establish KRG in Bremen.”

KRG will be led by Dr. Jakob Schwendner as managing director. Schwendner spent 10 years at DFKI, (the German Research Center for Artificial Intelligence) as an expert in autonomy, systems and software engineering for robotics, mission management, SLAM navigation, embedded systems, sensor processing and sensor fusion.

Dr. Jakob Schwendner, managing director of Kraken Robotik GmbH, said: “While there has been marked progress in Autonomous Underwater Vehicle (AUV) development, we want to focus on advancing underwater robotic vehicle autonomy. KRG efforts will explore methods of deploying AUVs in a broader range of subsea docking applications, sensor fusion, big data analytics and machine learning. These technologies will make it simpler and cheaper to complete underwater tasks.”

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