This document, entitled “D3.4 – AI-PRISM Human Centred Collaborative Robotic Platform (IV)”, contains the final description of the software developed and released during the AI-Prism project, from M7 to M39. It includes the definition of the software versions of the robotic framework, ambient digitalization, real-time communications and collaborative simulation released during these months.
Previous Versions
🡪 Building a distributed and calibrated network of sensors.
🡪 Novel models for the dynamic pose estimation of multiple people with respect to robot statuses.
🡪 Simplified deep graph partitioning method for detecting space-time patterns.
🡪 Techniques to classify and predict the future intention of operators based on accumulated behavioural data and the evolving context of processes and the environment.
Result:
🡪 Enhancing the global perception and reducing uncertainties in person tracking and modelling.
🡪 New AI techniques such as Deep Learning (DL) or the evolution of RL towards DRL (Deep Reinforcement Learning) to make these systems more autonomous with a degree of understanding of the world.
🡪 Intrinsic aspects of robot design, giving rise to cobots and AI-based central controllers that will avoid any dangerous situation.
Result:
🡪 Safety and security in manufacturing between people and robots, avoiding collision and limiting impact forces to acceptable levels.
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