activity
20142023
most citedLearning Agile Soccer Skills for a Bipedal Robot with Deep Reinforcement Learning

166 citations · 645 across the 36 of their papers we have counts for

collaborators
Showing cs.ROShow all

38 papers · 1 filter

cs.RO2023★ 9 cited

RoboCat: A Self-Improving Generalist Agent for Robotic Manipulation

Konstantinos Bousmalis, Giulia Vezzani, Dushyant Rao +36

The ability to leverage heterogeneous robotic experience from different robots and tasks to quickly master novel skills and embodiments has the potential to transform robot learnin…

cs.RO2023★ 13 cited

Barkour: Benchmarking Animal-level Agility with Quadruped Robots

Ken Caluwaerts, Atil Iscen, J. Chase Kew +41

Animals have evolved various agile locomotion strategies, such as sprinting, leaping, and jumping. There is a growing interest in developing legged robots that move like their biol…

cs.RO2023★ 166 cited

Learning Agile Soccer Skills for a Bipedal Robot with Deep Reinforcement Learning

Tuomas Haarnoja, Ben Moran, Guy Lever +25

We investigate whether Deep Reinforcement Learning (Deep RL) is able to synthesize sophisticated and safe movement skills for a low-cost, miniature humanoid robot that can be compo…

cs.RO2022★ 1 cited

NeRF2Real: Sim2real Transfer of Vision-guided Bipedal Motion Skills using Neural Radiance Fields

Arunkumar Byravan, Jan Humplik, Leonard Hasenclever +8

We present a system for applying sim2real approaches to "in the wild" scenes with realistic visuals, and to policies which rely on active perception using RGB cameras. Given a shor…

cs.RO2021★ 16 cited

Beyond Pick-and-Place: Tackling Robotic Stacking of Diverse Shapes

Alex X. Lee, Coline Devin, Yuxiang Zhou +18

We study the problem of robotic stacking with objects of complex geometry. We propose a challenging and diverse set of such objects that was carefully designed to require strategie…

cs.RO2021★ 2 cited

iCub

Lorenzo Natale, Chiara Bartolozzi, Francesco Nori +2

In this chapter we describe the history and evolution of the iCub humanoid platform. We start by describing the first version as it was designed during the RobotCub EU project and…

cs.RO2021★ 4 cited

A Plenum-Based Calibration Device for Tactile Sensor Arrays

Joan Kangro, Anand Vazhapilli Sureshbabu, Silvio Traversaro +2

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…

cs.RO2020★ 1 cited

"What, not how": Solving an under-actuated insertion task from scratch

Giulia Vezzani, Michael Neunert, Markus Wulfmeier +7

Robot manipulation requires a complex set of skills that need to be carefully combined and coordinated to solve a task. Yet, most ReinforcementLearning (RL) approaches in robotics…

cs.RO2020★ 13 cited

Learning Dexterous Manipulation from Suboptimal Experts

Rae Jeong, Jost Tobias Springenberg, Jackie Kay +5

Learning dexterous manipulation in high-dimensional state-action spaces is an important open challenge with exploration presenting a major bottleneck. Although in many cases the le…

cs.RO2019★ 16 cited

Modelling Generalized Forces with Reinforcement Learning for Sim-to-Real Transfer

Rae Jeong, Jackie Kay, Francesco Romano +6

Learning robotic control policies in the real world gives rise to challenges in data efficiency, safety, and controlling the initial condition of the system. On the other hand, sim…

cs.RO2019★ 9 cited

Self-Supervised Sim-to-Real Adaptation for Visual Robotic Manipulation

Rae Jeong, Yusuf Aytar, David Khosid +5

Collecting and automatically obtaining reward signals from real robotic visual data for the purposes of training reinforcement learning algorithms can be quite challenging and time…

cs.RO2018

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

Francisco Javier Andrade Chavez, Gabriele Nava, Silvio Traversaro +2

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…

cs.RO2018

Towards Partner-Aware Humanoid Robot Control Under Physical Interactions

Yeshasvi Tirupachuri, Gabriele Nava, Claudia Latella +5

The topic of physical human-robot interaction received a lot of attention from the robotics community because of many promising application domains. However, studying physical inte…

cs.RO2018

Momentum-Based Topology Estimation of Articulated Objects

Yeshasvi Tirupachuri, Silvio Traversaro, Francesco Nori +1

Articulated objects like doors, drawers, valves, and tools are pervasive in our everyday unstructured dynamic environments. Articulation models describe the joint nature between th…

cs.RO2018★ 3 cited

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

Stefano Dafarra, Gabriele Nava, Marie Charbonneau +8

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 thr…

cs.RO2017

Contact Force and Joint Torque Estimation Using Skin

Francisco Javier Andrade Chavez, Joan Kangro, Silvio Traversaro +2

In this paper, we present algorithms to estimate external contact forces and joint torques using only skin, i.e. distributed tactile sensors. To deal with gaps between the tactile…

cs.RO2017

An Optimization Based Control Framework for Balancing and Walking: Implementation on the iCub Robot

Marie Charbonneau, Gabriele Nava, Francesco Nori +1

A whole-body torque control framework adapted for balancing and walking tasks is presented in this paper. In the proposed approach, centroidal momentum terms are excluded in favor…

cs.RO2017

Modeling and Control of Humanoid Robots in Dynamic Environments: iCub Balancing on a Seesaw

Gabriele Nava, Daniele Pucci, Nuno Guedelha +4

Forthcoming applications concerning humanoid robots may involve physical interaction between the robot and a dynamic environment. In such scenario, classical balancing and walking…

cs.RO2017

A Receding Horizon Push Recovery Strategy for Balancing the iCub Humanoid Robot

Stefano Dafarra, Francesco Romano, Francesco Nori

Balancing and reacting to strong and unexpected pushes is a critical requirement for humanoid robots. We recently designed a capture point based approach which interfaces with a mo…

cs.RO2017★ 24 cited

Torque-Controlled Stepping-Strategy Push Recovery: Design and Implementation on the iCub Humanoid Robot

Stefano Dafarra, Francesco Romano, Francesco Nori

One of the challenges for the robotics community is to deploy robots which can reliably operate in real world scenarios together with humans. A crucial requirement for legged robot…

cs.RO2017

Inverse, forward and other dynamic computations computationally optimized with sparse matrix factorizations

Francesco Nori

We propose an algorithm to compute the dynamics of articulated rigid-bodies with different sensor distributions. Prior to the on-line computations, the proposed algorithm performs…

cs.RO2017

A Predictive Momentum-Based Whole-Body Torque Controller: Theory and Simulations for the iCub Stepping

Stefano Dafarra, Francesco Romano, Gabriele Nava +1

When balancing, a humanoid robot can be easily subjected to unexpected disturbances like external pushes. In these circumstances, reactive movements as steps become a necessary req…

cs.RO2017

Momentum Control of an Underactuated Flying Humanoid Robot

Daniele Pucci, Silvio Traversaro, Francesco Nori

The paper takes the first step towards the de- velopment of a control framework for underactuated flying humanoid robots. These robots may thus have the capacities of flight, conta…

cs.RO2017★ 19 cited

On Centroidal Dynamics and Integrability of Average Angular Velocity

Alessandro Saccon, Silvio Traversaro, Francesco Nori +1

In the literature on robotics and multibody dynamics, the concept of average angular velocity has received considerable attention in recent years. We address the question of whethe…