Zobrazeno 1 - 10
of 603
pro vyhledávání: '"A. P. Roveda"'
Autor:
Moroncelli, Angelo, Soni, Vishal, Shahid, Asad Ali, Maccarini, Marco, Forgione, Marco, Piga, Dario, Spahiu, Blerina, Roveda, Loris
Foundation models (FMs), large deep learning models pre-trained on vast, unlabeled datasets, exhibit powerful capabilities in understanding complex patterns and generating sophisticated outputs. However, they often struggle to adapt to specific tasks
Externí odkaz:
http://arxiv.org/abs/2410.16411
Autor:
Bazzi, Manuel Bianchi, Shahid, Asad Ali, Agia, Christopher, Alora, John, Forgione, Marco, Piga, Dario, Braghin, Francesco, Pavone, Marco, Roveda, Loris
The landscape of Deep Learning has experienced a major shift with the pervasive adoption of Transformer-based architectures, particularly in Natural Language Processing (NLP). Novel avenues for physical applications, such as solving Partial Different
Externí odkaz:
http://arxiv.org/abs/2409.11815
High-level synthesis (HLS) has significantly advanced the automation of digital circuits design, yet the need for expertise and time in pragma tuning remains challenging. Existing solutions for the design space exploration (DSE) adopt either heuristi
Externí odkaz:
http://arxiv.org/abs/2407.08797
Autor:
Shahid, Asad Ali, Narang, Yashraj, Petrone, Vincenzo, Ferrentino, Enrico, Handa, Ankur, Fox, Dieter, Pavone, Marco, Roveda, Loris
In recent years, deep reinforcement learning (RL) has shown its effectiveness in solving complex continuous control tasks like locomotion and dexterous manipulation. However, this comes at the cost of an enormous amount of experience required for tra
Externí odkaz:
http://arxiv.org/abs/2404.03336
Planning over discontinuous dynamics is needed for robotics tasks like contact-rich manipulation, which presents challenges in the numerical stability and speed of planning methods when either neural network or analytical models are used. On the one
Externí odkaz:
http://arxiv.org/abs/2310.04822
In everyday life collaboration tasks between human operators and robots, the former necessitate simple ways for programming new skills, the latter have to show adaptive capabilities to cope with environmental changes. The joint use of visual servoing
Externí odkaz:
http://arxiv.org/abs/2309.07729
Autor:
Franceschi, Paolo, Bertini, Fabio, Braghin, Francesco, Roveda, Loris, Pedrocchi, Nicola, Beschi, Manuel
This work addresses human intention identification during physical Human-Robot Interaction (pHRI) tasks to include this information in an assistive controller. To this purpose, human intention is defined as the desired trajectory that the human wants
Externí odkaz:
http://arxiv.org/abs/2307.10743
Knowledge distillation constitutes a potent methodology for condensing substantial neural networks into more compact and efficient counterparts. Within this context, softmax regression representation learning serves as a widely embraced approach, lev
Externí odkaz:
http://arxiv.org/abs/2304.11004
Technical debt occurs in many different forms across software artifacts. One such form is connected to software architectures where debt emerges in the form of structural anti-patterns across architecture elements, namely, architecture smells. As def
Externí odkaz:
http://arxiv.org/abs/2303.17862
Contact-rich manipulation involves kinematic constraints on the task motion, typically with discrete transitions between these constraints during the task. Allowing the robot to detect and reason about these contact constraints can support robust and
Externí odkaz:
http://arxiv.org/abs/2303.17481