87 citations · 452 across the 47 of their papers we have counts for
51 papers
All You Need Is Low Fidelity: Zero-Shot Sim-to-Real of Learned Robotic Fish Control
Liam Maloney, Simon Ramchandani, Mike Y. Michelis +2
Complex tasks for underwater robots remain limited by the capabilities of their controllers. Learning a better one for a soft, underactuated robotic fish trades simulator cost agai…
Fingers as Legs: Learning Self-Supported Locomotion and Manipulation with an Anthropomorphic Hand
Amirhossein Kazemipour, Hehui Zheng, Robert Katzschmann
A walking robotic hand must use the same fingers to move its body, support its weight, and interact with the environment. We show how an anthropomorphic hand can learn these skills…
Rapid Learning of Dexterous In-Hand Pen Writing through Real-Time Jacobian Estimation
Kai Stewart, Yasunori Toshimitsu, Robert K. Katzschmann
Dexterous in-hand manipulation of a grasped object with an anthropomorphic hand is an unsolved frontier for robot dexterity. The contact-richness and highly dynamic nature of objec…
Smooth Operator: A Real-Time Sampling-Based Algorithm for Kinematic Hand Retargeting
Robert Jomar Malate, Erik Bauer, Norica Bacuieti +4
Advances in learning-based robotic manipulation, such as Vision-Language-Action (VLA) models and Video Action Models (VAMs), heavily rely on high-quality teleoperation data. Their…
Learning Robust Dexterous In-Hand Manipulation from Joint Sensors with Proprioceptive Transformer
Senlan Yao, Chenyu Yang, Jaehoon Kim +2
In-hand object manipulation is a fundamental yet challenging capability for dexterous robots. Despite significant progress in dexterous manipulation, existing approaches rely heavi…
High-Speed, Scalable Sensor Readout for Dexterous Robotic Hands via Shift-Register Multiplexing
Jaehoon Kim, Lazaros Christoforidis, Michalis Papadakis +2
Dexterous robotic hands require high-speed multimodal sensing across many degrees of freedom, yet existing readout architectures often impose trade-offs between sensor count, wirin…
A Benchmark of Dexterity for Anthropomorphic Robotic Hands
Davide Liconti, Yuning Zhou, Yasunori Toshimitsu +2
Dexterity is a central yet ambiguously defined concept in the design and evaluation of anthropomorphic robotic hands. In practice, the term is often used inconsistently, with diffe…
Learning Actuator-Aware Spectral Submanifolds for Precise Control of Continuum Robots
Paul Leonard Wolff, Hugo Buurmeijer, Luis Pabon +6
Continuum robots exhibit high-dimensional, nonlinear dynamics which are often coupled with their actuation mechanism. Spectral submanifold (SSM) reduction has emerged as a leading…
A Unified Low-Dimensional Design Embedding for Joint Optimization of Shape, Material, and Actuation in Soft Robots
Vittorio Candiello, Manuel Mekkattu, Mike Y. Michelis +1
Soft robots achieve functionality through tight coupling among geometry, material composition, and actuation. As a result, effective design optimization requires these three aspect…
A Sensorless, Inherently Compliant Anthropomorphic Musculoskeletal Hand Driven by Electrohydraulic Actuators
Misato Sonoda, Ronan Hinchet, Amirhossein Kazemipour +2
Robotic manipulation in unstructured environments requires end-effectors that combine kinematic dexterity with physical compliance. While traditional rigid hands rely on complex ex…
Simple Models, Real Swimming: Digital Twins for Tendon-Driven Underwater Robots
Mike Y. Michelis, Nana Obayashi, Josie Hughes +1
Mimicking the graceful motion of swimming animals remains a core challenge in soft robotics due to the complexity of fluid-structure interaction and the difficulty of controlling s…
SERNF: Sample-Efficient Real-World Dexterous Policy Fine-Tuning via Action-Chunked Critics and Normalizing Flows
Chenyu Yang, Denis Tarasov, Davide Liconti +3
Real-world fine-tuning of dexterous manipulation policies remains challenging due to limited real-world interaction budgets and highly multimodal action distributions. Diffusion-ba…
Nonlinear Spectral Modeling and Control of Soft-Robotic Muscles from Data
Leonardo Bettini, Amirhossein Kazemipour, Robert K. Katzschmann +1
Artificial muscles are essential for compliant musculoskeletal robotics but complicate control due to nonlinear multiphysics dynamics. Hydraulically amplified electrostatic (HASEL)…
SORS: A Modular, High-Fidelity Simulator for Soft Robots
Manuel Mekkattu, Mike Y. Michelis, Robert K. Katzschmann
The deployment of complex soft robots in multiphysics environments requires advanced simulation frameworks that not only capture interactions between different types of material, b…
Decoupling Torque and Stiffness: A Unified Modeling and Control Framework for Antagonistic Artificial Muscles
Amirhossein Kazemipour, Robert K. Katzschmann
Antagonistic artificial muscles can decouple joint torque and stiffness, but contact transients often degrade this independence. We present a unified real-time framework applicable…
AquaROM: shape optimization pipeline for soft swimmers using parametric reduced order models
Mathieu Dubied, Paolo Tiso, Robert K. Katzschmann
The efficient optimization of actuated soft structures, particularly under complex nonlinear forces, remains a critical challenge in advancing robotics. Simulations of nonlinear st…
Robotic Assistant: Completing Collaborative Tasks with Dexterous Vision-Language-Action Models
Boshi An, Chenyu Yang, Robert Katzschmann
We adapt a pre-trained Vision-Language-Action (VLA) model (Open-VLA) for dexterous human-robot collaboration with minimal language prompting. Our approach adds (i) FiLM conditionin…
Beyond Anthropomorphism: Enhancing Grasping and Eliminating a Degree of Freedom by Fusing the Abduction of Digits Four and Five
Simon Fritsch, Liam Achenbach, Riccardo Bianco +9
This paper presents the SABD hand, a 16-degree-of-freedom (DoF) robotic hand that departs from purely anthropomorphic designs to achieve an expanded grasp envelope, enable manipula…
mimic-one: a Scalable Model Recipe for General Purpose Robot Dexterity
Elvis Nava, Victoriano Montesinos, Erik Bauer +8
We present a diffusion-based model recipe for real-world control of a highly dexterous humanoid robotic hand, designed for sample-efficient learning and smooth fine-motor action in…
Latent Action Diffusion for Cross-Embodiment Manipulation
Erik Bauer, Elvis Nava, Robert K. Katzschmann
End-to-end learning is emerging as a powerful paradigm for robotic manipulation, but its effectiveness is limited by data scarcity and the heterogeneity of action spaces across rob…
MAPLE: Encoding Dexterous Robotic Manipulation Priors Learned From Egocentric Videos
Alexey Gavryushin, Xi Wang, Robert J. S. Malate +5
Large-scale egocentric video datasets capture diverse human activities across a wide range of scenarios, offering rich and detailed insights into how humans interact with objects,…
ORCA: An Open-Source, Reliable, Cost-Effective, Anthropomorphic Robotic Hand for Uninterrupted Dexterous Task Learning
Clemens C. Christoph, Maximilian Eberlein, Filippos Katsimalis +8
General-purpose robots should possess human-like dexterity and agility to perform tasks with the same versatility as us. A human-like form factor further enables the use of vast da…
VQ-ACE: Efficient Policy Search for Dexterous Robotic Manipulation via Action Chunking Embedding
Chenyu Yang, Davide Liconti, Robert K. Katzschmann
Dexterous robotic manipulation remains a significant challenge due to the high dimensionality and complexity of hand movements required for tasks like in-hand manipulation and obje…
An Open-Source Soft Robotic Platform for Autonomous Aerial Manipulation in the Wild
Erik Bauer, Marc Blöchlinger, Pascal Strauch +3
Aerial manipulation combines the versatility and speed of flying platforms with the functional capabilities of mobile manipulation, which presents significant challenges due to the…