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Projects

COROMA (October 2016 - October 2019)

Andrea is a work package (WP) leader in the COROMA EU project. His WP research focuses on the safe and smart interaction between robots, humans and machines. Do you want to know more about COROMA? Watch this video:

 

SYMBIO-TIC (November 2015 - April 2019)

Project coordinator: prof. Lihui Wang.

The european manufacturing industry is facing challenges in terms of adaptability, flexibility and vertical integration. The SYMBIO-TIC project adresses these important issues towards a safe, dynamic, intuitive and cost effective working environment were inmersive and symbiotic collaboration between human workers and robots can take place and bring significant benefits to robot - reluctant industries, where current tasks and processes are thought too complex to be automated. The benefits that the project can bring about include lower costs, increased safety, better working conditions and higher profitability through improved adaptability, flexibility, performance and seamless integration.

Project specific objectives are:

  • Objective 1: To develop an active collision avoidance subsystem to safeguard human workers.
  • Objective 2: To generate adaptive task plans appropriate to both robots and human workers.
  • Objective 3: To adapt to dynamic changes with intuitive and multimodal programming.
  • Objective 4: To provide human workers with in-situ assistance on what-to-do and how-to-do.
  • Objective 5: To demonstrate and validate the project concept and solutions.

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Gesture-Based Password Recognition (January 2014 - Course DT2140 at KTH)

Authors: Andrea de Giorgio, Daniel Molin, Giulio Ceste, John Turesson.

Gesture based password recognition is an unexplored field of research based on the influence of two main areas: human gesture recognition in Human-Computer Interaction and password management in computer science. We took inspiration from new devices that will be soon commercialized and from latest publications in the field of human computer interaction to develop a sensor equipped glove for password generation through hand gestures. Our study shows that it is possible to store these passwords and to match them with an input password. The number of simultaneous changing variables within a single gesture is considerably high and the level of security of a password depends on both the accuracy and the number of sensors employed. Gesture based passwords does not provide a more secure way of password verification than alphanumeric passwords with our current setup. Although the encouraging results we obtained are based on a limited prototype, the soon available input devices based on hand movement that we found will bring more research to the field.


Profile picture of Andrea de Giorgio

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