Imagine a robot that doesn't just react to what it sees, but can 'imagine' what is happening behind a wall or guess how a person is feeling. It builds a mental map of the world to predict what might happen next, similar to how humans use intuition. This helps machines act more naturally and make smarter choices in unpredictable settings.
Current AI and robots often fail in complex social or unknown environments because they cannot account for 'invisible' factors like human emotions or hidden obstacles. This leads to low user acceptance and rigid, inefficient behavior.
An integrated computational architecture featuring a Reactive Layer for self-regulation, an Adaptive Layer for cognitive maps, and a Contextual Layer for memory, all linked to sensory and motor interfaces.
If you are a health coach provider dealing with rigid, non-adaptive patient guidance — this project developed a health coach decision tree system that improves user experience through better adaptability and legibility.
If you are a robot manufacturer dealing with machines that struggle in social settings — this project developed a social robotics architecture that uses empathy and behavioral matching to increase human user acceptance.
If you are a game developer dealing with predictable, boring NPC behavior — this project developed computer game benchmarks and virtualization models that allow agents to simulate future scenarios and act more realistically.
Based on available project data, there is no specific pricing model or licensing cost mentioned; the project received an EU contribution of EUR 3,132,460 for development.
The project includes 3 industry partners and tests use-cases in robotics and gaming, suggesting a path toward industrial application, though full-scale deployment data is not provided.
Based on available project data, specific IP or licensing agreements are not detailed in the summary.
The system integrates via a sensory acquisition interface for data input and a motor command interface for translating outputs into motion commands.
The project period runs from 2022-10-01 to 2026-09-30, indicating it is currently in the development and validation phase.
The consortium is research-heavy with 7 universities and 2 research institutes, but maintains a 25% industry ratio with 3 SMEs. This balance suggests the project is focused on high-level cognitive theory while ensuring practical application through SME involvement across 7 different countries.
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