"LEACON contributes to the advancement of state of the art in robotics within four main aspect:
1. A strategy to combine learning with reactive control, in order for robots to learn in a more robust way while avoiding irreversible events.
This research has been accepted both to ICRA (IEEE International Conference on Robotics and Automation) 2018 and Robotics and Automation Letters (RA-L).
2. The concept of cross-modal visuo-tactile perception has been introduced. Cross-modal perception allows a robot to gather knowledge with a sensing modality like vision, and to exploit such a knowledge using a second modality like touch. This way, the robot is able. for example, to gather knowledge of objects using vision, and, later, to recognize such objects by using only touch, without touching any objects before. This approach has to potential to enhance the flexibility of robot systems when working in unstructured environments, where the ability to change sensing modality is essential. The work has been accepted at ICRA 2017 and a journal extension with the latest is now preparation for IEEE Transactions on Robotics.
3. Two time and data-efficient approaches for recognition of human actions have been developed, called CODE and FADE. Using those approaches robots are able to recognize human actions.
CODE (COordination-based action DEscriptor) is based on a novel way to consider a similarity between two human whole-body actions based on how humans coordinate their body parts, while performing an action.
The CODE approach has been published in IEEE Robotics and Automation Letters (RA-L) and invited for presentation at ICRA 2017.
FADE, on the other hand, is a frequency-based approach. It leverages the properties that human motion cannot have significant frequency components higher than 15 Hz.
FADE has been published in Autonomous Robots and at the International Conference on Intelligent Robots and Systems (IROS 2016).
4. An approach for learning based on trial and error, PI-REM, has been developed. It aims at increasing the data efficiency leveraging approximated prior knowledge.
The work has been published at IROS 2017 and a journal paper is now in preparation.
The work carried out within LEACON has been published in important journals (RA-L, Autonomous Robots) and conferences (ICRA and IROS).
A workshop and a special issue were organized to further discuss the topic within the scientific community. During the ""tag der fakultät"" at the Technical University of Munich, the topics of LEACON were disseminated outside the scientific community.
The resaercher designed and was lecturer of the class ""Reinforcement Learning for Robotics"", which is based on the research activities of LEACON.
It is one of first classes worldwide that covers theory of trajectory-oriented reinforcement laerning applied to robotics, emphasizing the connection between learning and optimal control.
Due to its success, the class will be given also the next years within Prof. Lee´s chair.
As further dissemination activities, the researcher organized with Dr. Fanny Ficuciello and Dr. Sylvain Calinon the workshop: ""Learning and Control for Autonomous Manipulation Systems: the Role of Dimensionality Reduction"" held at ICRA 2017 and he was guest editor of the RA-L special issue associated to the workshop.
Thanks to the research results achieved within LEACON, Dr. Falco was offered and accepted a position at ABB, Corporate Research in Västerås, Sweden as a tenured senior scientist and project manager.
Therefore, the methodologies and skill acquired in LEACON have a direct impact both on researcher´s career and on the robots of the future both in flexible manufacturing and service robotics.
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