166 citations · 645 across the 36 of their papers we have counts for
44 papers
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…
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…
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…
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…
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…
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…
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…
"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…
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…
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…
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…
Simultaneously Learning Vision and Feature-based Control Policies for Real-world Ball-in-a-Cup
Devin Schwab, Tobias Springenberg, Murilo F. Martins +7
We present a method for fast training of vision based control policies on real robots. The key idea behind our method is to perform multi-task Reinforcement Learning with auxiliary…
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…
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…
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…
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…
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…
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…
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…
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…
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…
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…
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…
Momentum Control of Humanoid Robots with Series Elastic Actuators
Gabriele Nava, Daniele Pucci, Francesco Nori
Humanoid robots may require a degree of compliance at the joint level for improving efficiency, shock tolerance, and safe interaction with humans. The presence of joint elasticity,…