9 citations · 9 across the 8 of their papers we have counts for
7 papers · 1 filter
Augmenting Neural Networks-Based Model Approximators in Robotic Force-Tracking Tasks
Kevin Saad, Vincenzo Petrone, Enrico Ferrentino +3
As robotics gains popularity, interaction control becomes crucial for ensuring force tracking in manipulator-based tasks. Typically, traditional interaction controllers either requ…
ConceptBot: Enhancing Robot's Autonomy through Task Decomposition with Large Language Models and Knowledge Graph
Alessandro Leanza, Angelo Moroncelli, Giuseppe Vizzari +3
ConceptBot is a modular robotic planning framework that combines Large Language Models and Knowledge Graphs to generate feasible and risk-aware plans despite ambiguities in natural…
Toward Context-Aware Exoskeleton Assistance: Integrating Computer Vision Payload Estimation with a Multi-Metric Optimization Space
Andrea Dal Prete, Seyram Ofori, Chan Yon Sin +5
Back-support exoskeletons mitigate musculoskeletal strain, yet current systems rely on reactive sensing and lack context-aware assistance modulation. This paper presents a populati…
Robot Drummer: Learning Rhythmic Skills for Humanoid Drumming
Asad Ali Shahid, Francesco Braghin, Loris Roveda
Humanoid robots have seen remarkable advances in dexterity, balance, and locomotion, yet their role in expressive domains such as music performance remains largely unexplored. Musi…
RoboMorph: In-Context Meta-Learning for Robot Dynamics Modeling
Manuel Bianchi Bazzi, Asad Ali Shahid, Christopher Agia +6
The landscape of Deep Learning has experienced a major shift with the pervasive adoption of Transformer-based architectures, particularly in Natural Language Processing (NLP). Nove…
Nonlinear In-situ Calibration of Strain-Gauge Force/Torque Sensors for Humanoid Robots
Hosameldin Awadalla Omer Mohamed, Gabriele Nava, Punith Reddy Vanteddu +2
High force/torque (F/T) sensor calibration accuracy is crucial to achieving successful force estimation/control tasks with humanoid robots. State-of-the-art affine calibration mode…
Predicting human motion intention for pHRI assistive control
Paolo Franceschi, Fabio Bertini, Francesco Braghin +3
This work addresses human intention identification during physical Human-Robot Interaction (pHRI) tasks to include this information in an assistive controller. To this purpose, hum…