Cognibotics

About Cognibotics

Cognibotics, established in 2013, operates as a deep-tech robotics company originating as a spin-off from the RobotLab at Lund University in Sweden. The company was founded by Klas Nilsson, Bjorn Olofsson, Olof Sornmo, and Adam Nilsson, stemming from research conducted during a three-year EU project on industrial robot control. Klas Nilsson, the current CTO, brought experience from ABB and his research at the university, driven by the goal of delegating heavy, repetitive, or harmful work to user-friendly robots. The firm has secured approximately $9.93 million in funding over four rounds from investors including Fairpoint Capital, the European Union, and EIC Fund, which will support product marketing, customer-specific solution creation, and organizational expansion.

Cognibotics addresses fundamental limitations in industrial automation by developing both advanced hardware and intelligent software. The business model encompasses software licensing for its motion intelligence, IP licensing for OEM integration, and strategic partnerships. Its product lineup targets the manufacturing, logistics, and e-commerce industries, with applications in the automotive, aerospace, and energy sectors. The company generates revenue by offering packaged solutions to enhance the performance of third-party industrial robots and by developing its own state-of-the-art robotic systems.

A core part of the company's offering is its technology stack, which features robot hardware, control algorithms, and interactive motion programming. This includes the Juliet & Romeo® platform, which provides a generic, low-latency robot programming language with automatic memory management. For hardware, Cognibotics has developed the SigmaTau robot for high-speed machining of large parts and the HKM1800 for high-speed, long-reach pick-and-place tasks in warehouse automation. The company also provides calibration and accuracy solutions that improve the precision and consistency of industrial robots and cobots, effectively compensating for wear and tear to extend their operational life. A key design principle is energy efficiency, achieved through lightweight robot designs, like the parallel kinematic machine (PKM) based SigmaTau, and intelligent software that optimizes movement to reduce energy consumption and mechanical stress.