Tesi etd-04092013-101516 |
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Tipo di tesi
Tesi di laurea magistrale
Autore
CORUCCI, FRANCESCO
URN
etd-04092013-101516
Titolo
Robotic perception and control for a demolition task in unstructured environments
Dipartimento
INGEGNERIA DELL'INFORMAZIONE
Corso di studi
INGEGNERIA INFORMATICA
Relatori
relatore Prof. Avizzano, Carlo Alberto
relatore Prof. Frisoli, Antonio
relatore Prof. Ruffaldi, Emanuele
relatore Prof. Frisoli, Antonio
relatore Prof. Ruffaldi, Emanuele
Parole chiave
- cognitive robotics
- computer vision
- demolition robotics
- mobile robots
- percezione robotica
- robotic perception
- robotica cognitiva
- robotica mobile
- robots per demolizioni
Data inizio appello
09/05/2013
Consultabilità
Parziale
Data di rilascio
09/05/2053
Riassunto
The construction industry is a capital-intensive sector that has steadily turned towards mechanized and automated solutions in the last few decades. However, due to some specificities of this field, it is still technologically behind other sectors, like manufacturing: there is room for improvements, that could lead to economical, technical, and also social benefits.
In this work we focus on demolition robotics: taking the task of demolishing a wall as a case study (related to the needs of an industrial partner of our laboratory), we propose a mockup for studying perceptual and control aspects on a scaled-down representative scenario. The thesis deals with several aspects of the demolition task, ranging from perception, to planning, to human-robot interaction (HRI). In addition to a conceptual framework, we propose some new approaches to scene segmentation and situational awareness in unstructured environments, as well as an intuitive on-site HRI paradigm.
In this work we focus on demolition robotics: taking the task of demolishing a wall as a case study (related to the needs of an industrial partner of our laboratory), we propose a mockup for studying perceptual and control aspects on a scaled-down representative scenario. The thesis deals with several aspects of the demolition task, ranging from perception, to planning, to human-robot interaction (HRI). In addition to a conceptual framework, we propose some new approaches to scene segmentation and situational awareness in unstructured environments, as well as an intuitive on-site HRI paradigm.
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