374 citations · 1k across the 27 of their papers we have counts for
23 papers · 1 filter
Customizing Textile and Tactile Skins for Interactive Industrial Robots
Bo Ying Su, Zhongqi Wei, James McCann +2
Tactile skins made from textiles enhance robot-human interaction by localizing contact points and measuring contact forces. This paper presents a solution for rapidly fabricating,…
Estimating Properties of Solid Particles Inside Container Using Touch Sensing
Xiaofeng Guo, Hung-Jui Huang, Wenzhen Yuan
Solid particles, such as rice and coffee beans, are commonly stored in containers and are ubiquitous in our daily lives. Understanding those particles' properties could help us mak…
Cable Routing and Assembly using Tactile-driven Motion Primitives
Achu Wilson, Helen Jiang, Wenzhao Lian +1
Manipulating cables is challenging for robots because of the infinite degrees of freedom of the cables and frequent occlusion by the gripper and the environment. These challenges a…
Toward Zero-Shot Sim-to-Real Transfer Learning for Pneumatic Soft Robot 3D Proprioceptive Sensing
Uksang Yoo, Hanwen Zhao, Alvaro Altamirano +2
Pneumatic soft robots present many advantages in manipulation tasks. Notably, their inherent compliance makes them safe and reliable in unstructured and fragile environments. Howev…
RobotSweater: Scalable, Generalizable, and Customizable Machine-Knitted Tactile Skins for Robots
Zilin Si, Tianhong Catherine Yu, Katrene Morozov +2
Tactile sensing is essential for robots to perceive and react to the environment. However, it remains a challenge to make large-scale and flexible tactile skins on robots. Industri…
PoseIt: A Visual-Tactile Dataset of Holding Poses for Grasp Stability Analysis
Shubham Kanitkar, Helen Jiang, Wenzhen Yuan
When humans grasp objects in the real world, we often move our arms to hold the object in a different pose where we can use it. In contrast, typical lab settings only study the sta…
Grasp Stability Prediction with Sim-to-Real Transfer from Tactile Sensing
Zilin Si, Zirui Zhu, Arpit Agarwal +2
Robot simulation has been an essential tool for data-driven manipulation tasks. However, most existing simulation frameworks lack either efficient and accurate models of physical i…
Understanding Dynamic Tactile Sensing for Liquid Property Estimation
Hung-Jui Huang, Xiaofeng Guo, Wenzhen Yuan
Humans perceive the world by interacting with objects, which often happens in a dynamic way. For example, a human would shake a bottle to guess its content. However, it remains a c…
Using Collocated Vision and Tactile Sensors for Visual Servoing and Localization
Arkadeep Narayan Chaudhury, Timothy Man, Wenzhen Yuan +1
Coordinating proximity and tactile imaging by collocating cameras with tactile sensors can 1) provide useful information before contact such as object pose estimates and visually s…
ShapeMap 3-D: Efficient shape mapping through dense touch and vision
Sudharshan Suresh, Zilin Si, Joshua G. Mangelson +2
Knowledge of 3-D object shape is of great importance to robot manipulation tasks, but may not be readily available in unstructured environments. While vision is often occluded duri…
Taxim: An Example-based Simulation Model for GelSight Tactile Sensors
Zilin Si, Wenzhen Yuan
Simulation is widely used in robotics for system verification and large-scale data collection. However, simulating sensors, including tactile sensors, has been a long-standing chal…
Improving Grasp Stability with Rotation Measurement from Tactile Sensing
Raj Kolamuri, Zilin Si, Yufan Zhang +2
Rotational displacement about the grasping point is a common grasp failure when an object is grasped at a location away from its center of gravity. Tactile sensors with soft surfac…
Challenges and Outlook in Robotic Manipulation of Deformable Objects
Jihong Zhu, Andrea Cherubini, Claire Dune +10
Deformable object manipulation (DOM) is an emerging research problem in robotics. The ability to manipulate deformable objects endows robots with higher autonomy and promises new a…
Simulation of Vision-based Tactile Sensors using Physics based Rendering
Arpit Agarwal, Tim Man, Wenzhen Yuan
Tactile sensing has seen a rapid adoption with the advent of vision-based tactile sensors. Vision-based tactile sensors provide high resolution, compact and inexpensive data to per…
Learning Hierarchical Control for Robust In-Hand Manipulation
Tingguang Li, Krishnan Srinivasan, Max Qing-Hu Meng +2
Robotic in-hand manipulation has been a long-standing challenge due to the complexity of modelling hand and object in contact and of coordinating finger motion for complex manipula…
Learning an Action-Conditional Model for Haptic Texture Generation
Negin Heravi, Wenzhen Yuan, Allison M. Okamura +1
Rich haptic sensory feedback in response to user interactions is desirable for an effective, immersive virtual reality or teleoperation system. However, this feedback depends on ma…
Real-time Soft Body 3D Proprioception via Deep Vision-based Sensing
Ruoyu Wang, Shiheng Wang, Songyu Du +3
Soft bodies made from flexible and deformable materials are popular in many robotics applications, but their proprioceptive sensing has been a long-standing challenge. In other wor…
More Than a Feeling: Learning to Grasp and Regrasp using Vision and Touch
Roberto Calandra, Andrew Owens, Dinesh Jayaraman +5
For humans, the process of grasping an object relies heavily on rich tactile feedback. Most recent robotic grasping work, however, has been based only on visual input, and thus can…
ViTac: Feature Sharing between Vision and Tactile Sensing for Cloth Texture Recognition
Shan Luo, Wenzhen Yuan, Edward Adelson +2
Vision and touch are two of the important sensing modalities for humans and they offer complementary information for sensing the environment. Robots could also benefit from such mu…
Active Clothing Material Perception using Tactile Sensing and Deep Learning
Wenzhen Yuan, Yuchen Mo, Shaoxiong Wang +1
Humans represent and discriminate the objects in the same category using their properties, and an intelligent robot should be able to do the same. In this paper, we build a robot s…
The Feeling of Success: Does Touch Sensing Help Predict Grasp Outcomes?
Roberto Calandra, Andrew Owens, Manu Upadhyaya +4
A successful grasp requires careful balancing of the contact forces. Deducing whether a particular grasp will be successful from indirect measurements, such as vision, is therefore…
Improved GelSight Tactile Sensor for Measuring Geometry and Slip
Siyuan Dong, Wenzhen Yuan, Edward Adelson
A GelSight sensor uses an elastomeric slab covered with a reflective membrane to measure tactile signals. It measures the 3D geometry and contact force information with high spacia…
Shape-independent Hardness Estimation Using Deep Learning and a GelSight Tactile Sensor
Wenzhen Yuan, Chenzhuo Zhu, Andrew Owens +2
Hardness is among the most important attributes of an object that humans learn about through touch. However, approaches for robots to estimate hardness are limited, due to the lack…