1 citations · 1 across the 14 of their papers we have counts for
18 papers
ACTS: Learning Visuo-Tactile World Models from Human Physical Interaction
Yuxiang Ma, Weihan Xu, Pengfei Ye +5
Abstract Action-conditioned world models for contact-rich manipulation require data that captures how contact forms, slides, and releases under varying force. Such data are slow to…
Robot Learning with Visual Predicted Force
Haonan Chen, Feiyang Wu, Yuxiang Ma +11
Force-aware manipulation typically relies on specialized force or tactile sensors. We show that force-aware manipulation can instead be achieved through visual force prediction fro…
GlowTact: Simple and Compact Vision-Based Tactile Sensing with High Sensitivity and Spatial Resolution
Yuxiang Ma, Megha Tippur, Pengfei Ye +4
Vision-based tactile sensors (VBTS) provide rich contact information for robotic manipulation, but existing designs can be hard to simplify and adapt to the size and constraints of…
A Durable Vision-Based Tactile Fingertip for Robotic Manipulation
F. Richard Cottrell, Megha H. Tippur, Edward H. Adelson
Currently available commercial vision-based tactile sensors provide rich contact information but remain vulnerable to abrasion and repeated concentrated loading, limiting their use…
You Only Touch Once: 6-DoF Object Pose Estimation from Single Tactile Contact
Pengfei Ye, Yuxiang Ma, Haonan Chen +5
Accurate 6-DoF object pose estimation is fundamental to robotic manipulation, yet vision-based methods often fail under occlusion, poor lighting, and reflective or transparent surf…
CoStream: Composing Simple Behaviors for Generalizable Complex Manipulation
Haonan Chen, Yuxiang Ma, Stephen Tian +7
Long-horizon, contact-rich complex manipulation tasks, such as seating a GPU into a PCIe slot, demand both millimeter high precision and out-of-the-box generalization to new tasks.…
2D and 3D Grasp Planners for the GET Asymmetrical Gripper
Andrew Goldberg, Ethan Ransing, Anton Kourakin +3
In this paper, we introduce GET-2D-1.0, a fast grasp planner for the GET asymmetrical gripper that operates from a single-view RGB-D image, using the Ferrari-Canny metric and a nov…
ManipulationNet: An Infrastructure for Benchmarking Real-World Robot Manipulation with Physical Skill Challenges and Embodied Multimodal Reasoning
Yiting Chen, Kenneth Kimble, Edward H. Adelson +20
Dexterous manipulation enables robots to purposefully alter the physical world, transforming them from passive observers into active agents in unstructured environments. This capab…
Sashimi-Bot: Autonomous Tri-manual Advanced Manipulation and Cutting of Deformable Objects
Sverre Herland, Amit Parag, Elling Ruud Øye +9
Advanced robotic manipulation of deformable, volumetric objects remains one of the greatest challenges due to their pliancy, frailness, variability, and uncertainties during intera…
Object Recognition and Force Estimation with the GelSight Baby Fin Ray
Sandra Q. Liu, Yuxiang Ma, Edward H. Adelson
Recent advances in soft robotic hands and tactile sensing have enabled both to perform an increasing number of complex tasks with the aid of machine learning. In particular, we pre…
DEXOP: A Device for Robotic Transfer of Dexterous Human Manipulation
Hao-Shu Fang, Branden Romero, Yichen Xie +9
We introduce perioperation, a paradigm for robotic data collection that sensorizes and records human manipulation while maximizing the transferability of the data to real robots. W…
Grasp EveryThing (GET): 1-DoF, 3-Fingered Gripper with Tactile Sensing for Robust Grasping
Michael Burgess, Edward H. Adelson
We introduce the Grasp EveryThing (GET) gripper, a novel 1-DoF, 3-finger design for securely grasping objects of many shapes and sizes. Mounted on a standard parallel jaw actuator,…
PolyTouch: A Robust Multi-Modal Tactile Sensor for Contact-rich Manipulation Using Tactile-Diffusion Policies
Jialiang Zhao, Naveen Kuppuswamy, Siyuan Feng +2
Achieving robust dexterous manipulation in unstructured domestic environments remains a significant challenge in robotics. Even with state-of-the-art robot learning methods, haptic…
RainbowSight: A Family of Generalizable, Curved, Camera-Based Tactile Sensors For Shape Reconstruction
Megha H. Tippur, Edward H. Adelson
Camera-based tactile sensors can provide high resolution positional and local geometry information for robotic manipulation. Curved and rounded fingers are often advantageous, but…
EyeSight Hand: Design of a Fully-Actuated Dexterous Robot Hand with Integrated Vision-Based Tactile Sensors and Compliant Actuation
Branden Romero, Hao-Shu Fang, Pulkit Agrawal +1
In this work, we introduce the EyeSight Hand, a novel 7 degrees of freedom (DoF) humanoid hand featuring integrated vision-based tactile sensors tailored for enhanced whole-hand ma…
Transferable Tactile Transformers for Representation Learning Across Diverse Sensors and Tasks
Jialiang Zhao, Yuxiang Ma, Lirui Wang +1
This paper presents T3: Transferable Tactile Transformers, a framework for tactile representation learning that scales across multi-sensors and multi-tasks. T3 is designed to overc…
A Passively Bendable, Compliant Tactile Palm with RObotic Modular Endoskeleton Optical (ROMEO) Fingers
Sandra Q. Liu, Edward H. Adelson
Many robotic hands currently rely on extremely dexterous robotic fingers and a thumb joint to envelop themselves around an object. Few hands focus on the palm even though human han…
GelLink: A Compact Multi-phalanx Finger with Vision-based Tactile Sensing and Proprioception
Yuxiang Ma, Jialiang Zhao, Edward Adelson
Compared to fully-actuated robotic end-effectors, underactuated ones are generally more adaptive, robust, and cost-effective. However, state estimation for underactuated hands is u…