Skip to main content
Go to the home page of the European Commission (opens in new window)
English en
CORDIS - EU research results
CORDIS

Foundation AGI model for Industrial Robots

Project description

Intelligent robots move beyond pick-and-place

Robotics for automation has traditionally focused on performing pick-and-place tasks. Significant advancements in recent years have substantially increased their potential for more complex tasks and environments. However, current automation solutions struggle to operate in situations with increased variability or complexity, which are frequently present in manufacturing and warehouse logistics. The EIC-funded HYPER project will develop a next-generation artificial intelligence that addresses current challenges, including the lack of structured world models, robustness, online interaction, and multi-step reasoning and planning, thereby overcoming them. The project will build a foundation model for robots that learns online and can control any robot hardware using any sensors or data sources for input, thus learning by doing and continuously improving.

Objective

Today's automation solutions excel in structured environments but fail in complex and variable situations, significantly impacting industries like manufacturing and warehouse logistics. Robotics has traditionally focused on pick-and-place tasks because they provide a foundational basis for automation. Mastering these tasks allows for the generalization of solutions to other industrial automation applications. However, automating unstructured and unpredictable environments remains a significant challenge, requiring greater flexibility and adaptability in he supply chain.

To disrupt the automation industry SICS is developing next-generation AI that addresses the limitations of today’s AI and solves key problems of: 1) Lack of robustness; 2) Lack of structured world model; 3) Lack of online interaction; 4) Lack of multi-step reasoning and planning. At best, the step-by-step reasoning in today’s AI is based on statistical pattern recognition rather than true reasoning. SICS's objective is to build a foundation model for robots, a more general AI that learns online and can control any type of robot hardware independent of geometry and kinematics, using any type of sensors and data sources as input. This will allow robots to “learn by doing” and have an inherent continuous improvement where every interaction with the world is training the system, much like human learning.

With support and financing from EIC, we will be able to boost the development and lower the threshold for VCs to co-invest alongside EIC. The funding will also play an important role in independent external quality approval and a granted application will serve as a due diligence that increases the trust and lower the threshold for investors to engage.

Fields of science (EuroSciVoc)

Keywords

Programme(s)

Topic(s)

Funding Scheme

HORIZON-EIC-ACC - HORIZON EIC Accelerator

See all projects funded under this funding scheme

Call for proposal

(opens in new window) HORIZON-EIC-2024-ACCELERATOR-02

See all projects funded under this call

Coordinator

Superintelligence Computing Systems SICSAI AB
Net EU contribution
€ 2 389 165,64
Address
c/o KIVRA: 559229-3905
106 31 Stockholm
Sweden
SME
Yes
Region
Östra Sverige Stockholm Stockholms län
Activity type
Private for-profit entities (excluding Higher or Secondary Education Establishments)
Links
Total cost
No data