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Daniele Pucci

51 accepted papers

2026

Adaptive Non-Linear Centroidal MPC with Stability Guarantees for Robust Locomotion of Legged Robots

Mohamed Elobaid, Giulio Turrisi, Lorenzo Rapetti, Giulio Romualdi, Stefano Dafarra, Tomohiro Kawakami +4
ICRA 2026poster

Nonlinear model predictive locomotion controllers based on the reduced centroidal dynamics are nowadays ubiquitous in legged robots. These schemes, even if they assume an inherent simplification of the robot’s dynamics, were shown to endow robots with a step-adjustment capability in reaction to smal…

Cited by 0Source ↗PDF ↗Scholar ↗
2026

Contact-Aware Morphology Optimization via Physically Consistent Differentiable Simulation

Filippo Luca Ferretti, Diego Ferigo, Alessandro Croci, Carlotta Sartore, Omar G. Younis, Silvio Traversaro +1
RA-L 2026

Optimizing robot morphology and behavior remains an open challenge, primarily because hardware parameters affect system and contact dynamics, and naive parametrization can yield physically inconsistent designs and unreliable gradients. We propose a simulation-based co-design approach for gradient-ba

Cited by 0Source ↗Scholar ↗
2026

Robust by Co-Design: CAD-to-Control Evolutionary Optimization of Jet-Powered Humanoids

Punith Reddy Vanteddu, Davide Gorbani, Antonello Paolino, Giuseppe L'Erario, Hosameldin Awadalla Omer Mohamed, Fabio Bergonti +1
RA-L 2026

This letter presents a co-design and optimization framework for improving robustness in an aerial humanoid equipped with variable turbine configurations. The approach integrates CAD-based modeling, domain randomization, and multi-objective evolutionary optimization to jointly explore turbine placeme

Cited by 0Source ↗Scholar ↗
2025

Adaptive Non-Linear Centroidal MPC With Stability Guarantees for Robust Locomotion of Legged Robots

Mohamed Elobaid, Giulio Turrisi, Lorenzo Rapetti, Giulio Romualdi, Stefano Dafarra, Tomohiro Kawakami +4
RA-L 2025

Nonlinear model predictive locomotion controllers based on the reduced centroidal dynamics are nowadays ubiquitous in legged robots. These schemes, even if they assume an inherent simplification of the robot's dynamics, were shown to endow robots with a step-adjustment capability in reaction to smal

Cited by 10Source ↗Scholar ↗
2025

Maximising Tolerance to Disturbances via Combined Control-Actuation Optimisation for Robust Humanoid Robot Walking

Akhil Sathuluri, Carlotta Sartore, Stefano Dafarra, Silvio Traversaro, Markus Zimmermann, Daniele Pucci
RA-L 2025

Combined optimisation of various robot subsystems as a co-design problem has been shown to identify performant robots. However, classical optimisation methods result in point-optimum solutions that may not ensure robust performance and physical feasibility, i.e., the existence of components with spe

Cited by 1Source ↗Scholar ↗
2025

Multi-Objective Optimization of Humanoid Robot Hardware and Control for Multiple Tasks via Genetic Algorithms

Carlotta Sartore, Silvio Traversaro, Daniele Pucci
IROS 2025

The optimization of hardware and control of humanoid robots for multiple tasks is still an open challenge due to the competing objectives of different behaviors and the complexity of considering control architectures at the design level of a humanoid robot. In this work, we propose a unified multi-o

Cited by 0Source ↗Scholar ↗
2025

Online Nonlinear MPC for Multimodal Locomotion

Saverio Taliani, Gabriele Nava, Giuseppe L'Erario, Mohamed Elobaid, Giulio Romualdi, Daniele Pucci
ICRA 2025

Aerial humanoid robots can enhance the efficiency and safety of rescue operations in disaster scenarios. The control of such complex machines presents many challenges, for instance, the control of the different locomotion strategies and the stabilization of the transition maneuvers. In this article,

Cited by 1Source ↗Scholar ↗
2025

Physics-Informed Learning for Human Whole-Body Kinematics Prediction via Sparse IMUs

Cheng Guo, Giuseppe L'Erario, Giulio Romualdi, Mattia Leonori, Marta Lorenzini, Arash Ajoudani +1
IROS 2025

Accurate and physically feasible human motion prediction is crucial for safe and seamless human-robot collaboration. While recent advancements in human motion capture enable real-time pose estimation, the practical value of many existing approaches is limited by the lack of future predictions and co

Cited by 0Source ↗Scholar ↗
2025

Physics-Informed Neural Networks With Unscented Kalman Filter for Sensorless Joint Torque Estimation in Humanoid Robots

Ines Sorrentino, Giulio Romualdi, Lorenzo Moretti, Silvio Traversaro, Daniele Pucci
RA-L 2025

This paper presents a novel framework for whole-body torque control of humanoid robots without joint torque sensors, designed for systems with electric motors and high-ratio harmonic drives. The approach integrates Physics-Informed Neural Networks (PINNs) for friction modeling and Unscented Kalman F

Cited by 6Source ↗Scholar ↗
2025

Stabilizing Humanoid Robot Trajectory Generation via Physics-Informed Learning and Control-Informed Steering

Evelyn D'Elia, Paolo Maria Viceconte, Lorenzo Rapetti, Diego Ferigo, Giulio Romualdi, Giuseppe L'Erario +2
IROS 2025

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 these approaches make more realistic motions possible, they are limited by the amount of available motion data, and do not

Cited by 0Source ↗Scholar ↗
2024

Co-Design Optimisation of Morphing Topology and Control of Winged Drones

Fabio Bergonti, Gabriele Nava, Valentin Wüest, Antonello Paolino, Giuseppe L’Erario, Daniele Pucci +1
ICRA 2024poster

The design and control of winged aircraft and drones is an iterative process aimed at identifying a compromise of mission-specific costs and constraints. When agility is required, shape-shifting (morphing) drones represent an efficient solution. However, morphing drones require the addition of actua…

Cited by 14Source ↗code ↗Scholar ↗
2024

From CAD to URDF: Co-Design of a Jet-Powered Humanoid Robot Including CAD Geometry

Punith Reddy Vanteddu, Gabriele Nava, Fabio Bergonti, Giuseppe L’Erario, Antonello Paolino, Daniele Pucci
IROS 2024poster

Co-design optimization strategies usually rely on simplified robot models extracted from CAD. While these models are useful for optimizing geometrical and inertial parameters for robot control, they might overlook important details essential for prototyping the optimized mechanical design. For insta…

Cited by 0Source ↗Scholar ↗
2024

Learning to Walk and Fly with Adversarial Motion Priors

Giuseppe L’Erario, Drew Hanover, Ángel Romero, Yunlong Song, Gabriele Nava, Paolo Maria Viceconte +2
IROS 2024poster

Robot multimodal locomotion encompasses the ability to transition between walking and flying, representing a significant challenge in robotics. This work presents an approach that enables automatic smooth transitions between legged and aerial locomotion. Leveraging the concept of Adversarial Motion…

Cited by 1Source ↗Scholar ↗
2024

XBG: End-to-End Imitation Learning for Autonomous Behaviour in Human-Robot Interaction and Collaboration

Carlos Cardenas-Perez, Giulio Romualdi, Mohamed Elobaid, Stefano Dafarra, Giuseppe L'Erario, Silvio Traversaro +3
RA-L 2024

This letter presents XBG (eXteroceptive Behaviour Generation), a multimodal end-to-end Imitation Learning (IL) system for whole-body autonomous humanoid robots used in real-world Human-Robot Interaction (HRI) scenarios. The main contribution is an architecture for learning HRI behaviours using a dat

Cited by 6Source ↗code ↗Scholar ↗
2023

A Control Approach for Human-Robot Ergonomic Payload Lifting

Lorenzo Rapetti, Carlotta Sartore, Mohamed Elobaid, Yeshasvi Tirupachuri, Francesco Draicchio, Tomohiro Kawakami +2
ICRA 2023poster

Collaborative robots can relief human operators from excessive efforts during payload lifting activities. Modelling the human partner allows the design of safe and efficient collaborative strategies. In this paper, we present a control approach for human-robot collaboration based on human monitoring…

Cited by 10Source ↗Scholar ↗
2023

Failure Detection and Fault Tolerant Control of a Jet-Powered Flying Humanoid Robot

Gabriele Nava, Daniele Pucci
ICRA 2023poster

Failure detection and fault tolerant control are fundamental safety features of any aerial vehicle. With the emer-gence of complex, multi-body flying systems such as jet-powered humanoid robots, it becomes of crucial importance to design fault detection and control strategies for these systems, too.…

Cited by 2Source ↗code ↗Scholar ↗
2023

Online Non-linear Centroidal MPC for Humanoid Robots Payload Carrying with Contact-Stable Force Parametrization

Mohamed Elobaid, Giulio Romualdi, Gabriele Nava, Lorenzo Rapetti, Hosameldin Awadalla Omer Mohamed, Daniele Pucci
ICRA 2023poster

In this paper we consider the problem of allowing a humanoid robot that is subject to a persistent disturbance, in the form of a payload-carrying task, to follow given planned footsteps. To solve this problem, we combine an online nonlinear centroidal Model Predictive Controller - MPC with a contact…

Cited by 9Source ↗code ↗Scholar ↗
2022

ADHERENT: Learning Human-like Trajectory Generators for Whole-body Control of Humanoid Robots

Paolo Maria Viceconte, Raffaello Camoriano, Giulio Romualdi, Diego Ferigo, Stefano Dafarra, Silvio Traversaro +3
RA-L 2022

<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Human-like</i> trajectory generation and footstep planning represent challenging problems in humanoid robotics. Recently, research in computer graphics investigated machine-learning methods for characte

Cited by 22Source ↗Scholar ↗
2022

Centroidal Aerodynamic Modeling and Control of Flying Multibody Robots

Tong Hui, Antonello Paolino, Gabriele Nava, Giuseppe L'Erario, Fabio Di Natale, Fabio Bergonti +2
ICRA 2022poster

This paper presents a modeling and control frame-work for multibody flying robots subject to non-negligible aero-dynamic forces acting on the centroidal dynamics. First, aero-dynamic forces are calculated during robot flight in different operating conditions by means of Computational Fluid Dynamics…

Cited by 7Source ↗Scholar ↗
2022

Comparison of EKF-Based Floating Base Estimators for Humanoid Robots with Flat Feet

Prashanth Ramadoss, Giulio Romualdi, Stefano Dafarra, Silvio Traversaro, Daniele Pucci
IROS 2022poster

Extended Kalman filtering is a common approach to achieve floating base estimation of a humanoid robot. These filters rely on measurements from an Inertial Measurement Unit (IMU) and relative forward kinematics for estimating the base position-and-orientation and its linear velocity along with the a…

Cited by 0Source ↗Scholar ↗
2022

Momentum-Based Extended Kalman Filter for Thrust Estimation on Flying Multibody Robots

Hosameldin Awadalla Omer Mohamed, Gabriele Nava, Giuseppe L'Erario, Silvio Traversaro, Fabio Bergonti, Luca Fiorio +3
RA-L 2022

Effective control design of flying vehicles requires a reliable estimation of the propellers’ thrust forces to secure a successful flight. Direct measurements of thrust forces, however, are seldom available in practice and on-line thrust estimation usually follows from the application of fusion algo

Cited by 25Source ↗Scholar ↗
2022

Nonlinear Model Identification and Observer Design for Thrust Estimation of Small-scale Turbojet Engines

Affaf Junaid Ahamad Momin, Gabriele Nava, Giuseppe L'Erario, Hosameldin Awadalla Omer Mohamed, Fabio Bergonti, Punith Reddy Vanteddu +2
ICRA 2022poster

Jet-powered vertical takeoff and landing (VTOL) drones require precise thrust estimation to ensure adequate stability margins and robust maneuvering. Small-scale turbojets have become good candidates for powering heavy aerial drones. However, due to limited instrumentation available in these turboje…

Cited by 8Source ↗Scholar ↗
2022

Online Non-linear Centroidal MPC for Humanoid Robot Locomotion with Step Adjustment

Giulio Romualdi, Stefano Dafarra, Giuseppe L'Erario, Ines Sorrentino, Silvio Traversaro, Daniele Pucci
ICRA 2022poster

This paper presents a Non-Linear Model Predictive Controller for humanoid robot locomotion with online step adjustment capabilities. The proposed controller considers the Centroidal Dynamics of the system to compute the desired contact forces and torques and contact locations. Differently from biped…

Cited by 58Source ↗code ↗Scholar ↗
2021

DILIGENT-KIO: A Proprioceptive Base Estimator for Humanoid Robots using Extended Kalman Filtering on Matrix Lie Groups

Prashanth Ramadoss, Giulio Romualdi, Stefano Dafarra, Francisco Javier Andrade Chavez, Silvio Traversaro, Daniele Pucci
ICRA 2021poster

This paper presents a contact-aided inertial-kinematic floating base estimation for humanoid robots considering an evolution of the state and observations over matrix Lie groups. This is achieved through the application of a geometrically meaningful estimator which is characterized by concentrated G…

Cited by 14Source ↗Scholar ↗
2021

Force Control With Friction Compensation In A Pneumatic Gripper

Rocco A. Romeo, Agata Zocco, Luca Fiorio, Daniele Pucci, M. Maggiali
IROS 2021poster

Robots can grasp, even manipulate, objects with different shape, weight and size thanks to the their end-effectors. These are mostly constituted by two fingers, and are known as grippers. However, despite being quite simple for human beings, manipulation is not so straightforward to carry out on rob…

Cited by 4Source ↗Scholar ↗
2021

In Situ Translational Hand-Eye Calibration of Laser Profile Sensors using Arbitrary Objects

Prajval Kumar Murali, Ines Sorrentino, Angelo Rendiniello, Claudio Fantacci, Enrico Villagrossi, Andrea Polo +5
ICRA 2021poster

Hand-eye calibration of laser profile sensors is the process of extracting the homogeneous transformation between the laser profile sensor frame and the end-effector frame of a robot in order to express the data extracted by the sensor in the robot’s global coordinate system. For laser profile scann…

Cited by 8Source ↗Scholar ↗
2021

On the Emergence of Whole-Body Strategies From Humanoid Robot Push-Recovery Learning

Diego Ferigo, Raffaello Camoriano, Paolo Maria Viceconte, Daniele Calandriello, Silvio Traversaro, Lorenzo Rosasco +1
RA-L 2021

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 simplified physical models and hard-coded strategies. Although successful in specific scenarios, this approach requires de

Cited by 22Source ↗Scholar ↗
2021

Shared Control of Robot-Robot Collaborative Lifting with Agent Postural and Force Ergonomic Optimization

Lorenzo Rapetti, Yeshasvi Tirupachuri, Alberto Ranavolo, Tomohiro Kawakami, Takahide Yoshiike, Daniele Pucci
ICRA 2021poster

Humans show specialized strategies for efficient collaboration. Transferring similar strategies to humanoid robots can improve their capability to interact with other agents, leading the way to complex collaborative scenarios with multiple agents acting on a shared environment. In this paper we pres…

Cited by 12Source ↗Scholar ↗
2020

Direct Force Feedback Control and Online Multi-Task Optimization for Aerial Manipulators

Gabriele Nava, Quentin Sablé, Marco Tognon, Daniele Pucci, Antonio Franchi
RA-L 2020

In this letter we present an optimization-based method for controlling aerial manipulators in physical contact with the environment. The multi-task control problem, which includes hybrid force-motion tasks, energetic tasks, and position/postural tasks, is recast as a quadratic programming problem wi

Cited by 75Source ↗Scholar ↗
2020

Dynamic Control of a Rigid Pneumatic Gripper

Rocco Antonio Romeo, Luca Fiorio, Giuseppe L'Erario, Marco Maggiali, Giorgio Metta, Daniele Pucci
RA-L 2020

Pneumatic grippers are hugely employed in robotic applications. Nonetheless, their control is not easy due to difficulty in managing the pressure inside their air chambers. Pneumatic grippers have often simple structure though the lack of affordable control algorithms complicates their usage. Motiva

Cited by 8Source ↗Scholar ↗
2020

Modeling, Identification and Control of Model Jet Engines for Jet Powered Robotics

Giuseppe L'Erario, Luca Fiorio, Gabriele Nava, Fabio Bergonti, Hosameldin Awadalla Omer Mohamed, Emilio Benenati +2
RA-L 2020

The paper contributes towards the modeling, identification, and control of model jet engines. We propose a nonlinear, second order model in order to capture the model jet engines governing dynamics. The model structure is identified by applying sparse identification of nonlinear dynamics, and then t

Cited by 25Source ↗Scholar ↗
2020

Non-Linear Trajectory Optimization for Large Step-Ups: Application to the Humanoid Robot Atlas

Stefano Dafarra, Sylvain Bertrand, Robert J. Griffin, Giorgio Metta, Daniele Pucci, Jerry Pratt
IROS 2020poster

Performing large step-ups is a challenging task for a humanoid robot. It requires the robot to perform motions at the limit of its reachable workspace while straining to move its body upon the obstacle. This paper presents a non-linear trajectory optimization method for generating step-up motions. W…

Cited by 23Source ↗Scholar ↗
2020

Whole-Body Walking Generation using Contact Parametrization: A Non-Linear Trajectory Optimization Approach

Stefano Dafarra, Giulio Romualdi, Giorgio Metta, Daniele Pucci
ICRA 2020poster

In this paper, we describe a planner capable of generating walking trajectories by using the centroidal dynamics and the full kinematics of a humanoid robot model. The interaction between the robot and the walking surface is modeled explicitly through a novel contact parametrization. The approach is…

Cited by 10Source ↗Scholar ↗
2019

Closed-loop Force Control of a Pneumatic Gripper Actuated by Two Pressure Regulators

Rocco A. Romeo, Luca Fiorio, Edwin J. Avila-Mireles, Ferdinando Cannella, Giorgio Metta, Daniele Pucci
IROS 2019poster

Robotic arms can perform grasping actions thanks to their “dexteorus” part, i.e. the gripper. Among the various categories, nowadays pneumatic grippers became the most employed in industry, as they have low cost and little bulkiness. Despite their simplicity, controlling the force applied by these g…

Cited by 6Source ↗Scholar ↗
2019

Learning to Sequence Multiple Tasks with Competing Constraints

Anqing Duan, Raffaello Camoriano, Diego Ferigo, Yanlong Huang, Daniele Calandriello, Lorenzo Rosasco +1
IROS 2019poster

Imitation learning offers a general framework where robots can efficiently acquire novel motor skills from demonstrations of a human teacher. While many promising achievements have been shown, the majority of them are only focused on single-stroke movements, without taking into account the problem o…

Cited by 8Source ↗Scholar ↗
2019

Model Based In Situ Calibration with Temperature compensation of 6 axis Force Torque Sensors

Francisco Javier Andrade Chavez, Gabriele Nava, Silvio Traversaro, Francesco Nori, Daniele Pucci
ICRA 2019poster

It is well known that sensors using strain gauges have a potential dependency on temperature. This creates temperature drift in the measurements of six axis force torque sensors (F/T). The temperature drift can be considerable if an experiment is long or the environmental conditions are different fr…

Cited by 17Source ↗Scholar ↗
2019

Torque and velocity controllers to perform jumps with a humanoid robot: theory and implementation on the iCub robot

Fabio Bergonti, Luca Fiorio, Daniele Pucci
ICRA 2019poster

Jumping can be an effective way of locomotion to overcome small terrain gaps or obstacles. In this paper we propose two different approaches to perform jumps with a humanoid robot. Specifically, starting from a pre-defined CoM trajectory we develop the theory for a velocity controller and for a torq…

Cited by 5Source ↗Scholar ↗
2018

A Control Architecture with Online Predictive Planning for Position and Torque Controlled Walking of Humanoid Robots

Stefano Dafarra, Gabriele Nava, Marie Charbonneau, Nuno Guedelha, Francisco Andrade, Silvio Traversaro +5
IROS 2018poster

A common approach to the generation of walking patterns for humanoid robots consists in adopting a layered control architecture. This paper proposes an architecture composed of three nested control loops. The outer loop exploits a robot kinematic model to plan the footstep positions. In the mid laye…

Cited by 20Source ↗Scholar ↗
2018

A Plenum-Based Calibration Device for Tactile Sensor Arrays

Joan Kangro, Anand Vazhapilli Sureshbabu, Silvio Traversaro, Daniele Pucci, Francesco Nori
RA-L 2018

In modern robotic applications, tactile sensor arrays (i.e., artificial skins) are an emergent solution to determine the locations of contacts between a robot and an external agent. Localizing the point of contact is useful but determining the force applied on the skin provides many additional possi

Cited by 6Source ↗Scholar ↗
2018

Contact Force and Joint Torque Estimation Using Skin

Francisco Javier Andrade Chavez, Joan Kangro, Silvio Traversaro, Francesco Nori, Daniele Pucci
RA-L 2018

In this letter, we present algorithms to estimate contact locations, external forces, and joint torques using skin, i.e., distributed tactile sensors, kinematic sensors, and a single Inertial Measurement Unit (IMU) without the need for force-torque sensors. Distributed tactile sensors are an array o

Cited by 11Source ↗Scholar ↗
2018

The CoDyCo Project Achievements and Beyond: Toward Human Aware Whole-Body Controllers for Physical Human Robot Interaction

Francesco Romano, Gabriele Nava, Morteza Azad, Jernej Camernik, Stefano Dafarra, Oriane Dermy +12
RA-L 2018

The success of robots in real-world environments is largely dependent on their ability to interact with both humans and said environment. The FP7 EU project CoDyCo focused on the latter of these two challenges by exploiting both rigid and compliant contacts dynamics in the robot control problem. Reg

Cited by 32Source ↗Scholar ↗
2016

Stability analysis and design of momentum-based controllers for humanoid robots

Gabriele Nava, Francesco Romano, Francesco Nori, Daniele Pucci
IROS 2016poster

Envisioned applications for humanoid robots call for the design of balancing and walking controllers. While promising results have been recently achieved, robust and reliable controllers are still a challenge for the control community dealing with humanoid robotics. Momentum-based strategies have pr…

Cited by 81Source ↗Scholar ↗
2015

In situ calibration of six-axis force-torque sensors using accelerometer measurements

Silvio Traversaro, Daniele Pucci, Francesco Nori
ICRA 2015poster

This paper proposes techniques to calibrate six-axis force-torque sensors that can be performed in situ, i.e., without removing the sensor from the hosting system. We assume that the force-torque sensor is attached to a rigid body equipped with an accelerometer. Then, the proposed calibration techni…

Cited by 35Source ↗Scholar ↗