65 citations · 89 across the 5 of their papers we have counts for
5 papers
Stabilizing Humanoid Robot Trajectory Generation via Physics-Informed Learning and Control-Informed Steering
Evelyn D'Elia, Paolo Maria Viceconte, Lorenzo Rapetti +5
Recent trends in humanoid robot control have successfully employed imitation learning to enable the learned generation of smooth, human-like trajectories from human data. While the…
Online DNN-driven Nonlinear MPC for Stylistic Humanoid Robot Walking with Step Adjustment
Giulio Romualdi, Paolo Maria Viceconte, Lorenzo Moretti +4
This paper presents a three-layered architecture that enables stylistic locomotion with online contact location adjustment. Our method combines an autoregressive Deep Neural Networ…
Learning to Walk and Fly with Adversarial Motion Priors
Giuseppe L'Erario, Drew Hanover, Angel Romero +5
Robot multimodal locomotion encompasses the ability to transition between walking and flying, representing a significant challenge in robotics. This work presents an approach that…
iCub3 Avatar System: Enabling Remote Fully-Immersive Embodiment of Humanoid Robots
Stefano Dafarra, Ugo Pattacini, Giulio Romualdi +18
We present an avatar system designed to facilitate the embodiment of humanoid robots by human operators, validated through iCub3, a humanoid developed at the Istituto Italiano di T…
On the Emergence of Whole-body Strategies from Humanoid Robot Push-recovery Learning
Diego Ferigo, Raffaello Camoriano, Paolo Maria Viceconte +4
Balancing and push-recovery are essential capabilities enabling humanoid robots to solve complex locomotion tasks. In this context, classical control systems tend to be based on si…