IBRICS
Imitating Human Behaviors by Robotic Systems through Computer Vision and Machine Learning
Abstract
The research project focuses on developing a system that combines Computer Vision, Machine Learning, and Optimization-based Control for analyzing and recognizing human behaviors in realistic environments, and transferring these behaviors to robotic systems. The aim is to create a system that enables robotic systems to imitate dynamic movements and behaviors through the processing of visual data and machine learning algorithms. The project contributes to the development of intelligent robotic agents that can interact effectively both with each other and with humans in real-world situations.
The project advances innovative technologies in four main directions: extraction of human body pose from images, analysis of 3D human motion, tracking of dynamic trajectories in 3D, and development of controllers for robot manipulation. The project leverages deep learning, reinforcement learning, and optimization-based control techniques, with the goal of developing robotic systems for industrial and other applications, such as human-robot collaboration.
The project is funded by Archimedes RC: it falls under the project MIS 5154714 of the National Recovery and Resilience Plan Greece 2.0 funded by the European Union under the NextGenerationEU Program.
More details to be added soon…
People
Konstantinos Chatzilygeroudis
Androutsopoulos Aristeidis
Tsiatsianas Evangelos
Ntagkas Alexandros
Lampros Printzios
