activity
20172026
most citedDeep Transfer Learning of Pick Points on Fabric for Robot Bed-Making

23 citations · 120 across the 18 of their papers we have counts for

collaborators

18 papers

cs.RO2026

Geometrically Plausible Object Pose Refinement using Differentiable Simulation

Anil Zeybek, Rhys Newbury, Snehal Dikhale +3

State-of-the-art object pose estimation methods are prone to generating geometrically infeasible pose hypotheses. This problem is prevalent in dexterous manipulation, where estimat…

cs.RO2026

VisuoTactile 6D Pose Estimation of an In-Hand Object using Vision and Tactile Sensor Data

Snehal s. Dikhale, Karankumar Patel, Daksh Dhingra +4

Knowledge of the 6D pose of an object can benefit in-hand object manipulation. In-hand 6D object pose estimation is challenging because of heavy occlusion produced by the robot's g…

cs.RO2024★ 4 cited

Social Mediation through Robots -- A Scoping Review on Improving Group Interactions through Directed Robot Action using an Extended Group Process Model

Thomas H. Weisswange, Hifza Javed, Manuel Dietrich +2

Group processes refer to the dynamics that occur within a group and are critical for understanding how groups function. With robots being increasingly placed within small groups, i…

cs.RO2024

HyperTaxel: Hyper-Resolution for Taxel-Based Tactile Signals Through Contrastive Learning

Hongyu Li, Snehal Dikhale, Jinda Cui +2

To achieve dexterity comparable to that of humans, robots must intelligently process tactile sensor data. Taxel-based tactile signals often have low spatial-resolution, with non-st…

cs.RO2023★ 16 cited

ViHOPE: Visuotactile In-Hand Object 6D Pose Estimation with Shape Completion

Hongyu Li, Snehal Dikhale, Soshi Iba +1

In this letter, we introduce ViHOPE, a novel framework for estimating the 6D pose of an in-hand object using visuotactile perception. Our key insight is that the accuracy of the 6D…

cs.RO2023★ 1 cited

"How Did They Come Across?" Lessons Learned from Continuous Affective Ratings

Maria Teresa Parreira, Michael J. Sack, Hifza Javed +2

Social distance, or perception of the other, is recognized as a dynamic dimension of an interaction, but yet to be widely explored or understood. Through CORAE, a novel web-based o…

cs.RO2023★ 4 cited

What Could a Social Mediator Robot Do? Lessons from Real-World Mediation Scenarios

Thomas H. Weisswange, Hifza Javed, Manuel Dietrich +4

The use of social robots as instruments for social mediation has been gaining traction in the field of Human-Robot Interaction (HRI). So far, the design of such robots and their be…

cs.RO2023★ 1 cited

Group Dynamics: Survey of Existing Multimodal Models and Considerations for Social Mediation

Hifza Javed, Nawid Jamali

Social mediator robots facilitate human-human interactions by producing behavior strategies that positively influence how humans interact with each other in social settings. As rob…

cs.RO2023

Modeling Group Dynamics for Personalized Robot-Mediated Interactions

Hifza Javed, Nawid Jamali

The field of human-human-robot interaction (HHRI) uses social robots to positively influence how humans interact with each other. This objective requires models of human understand…

cs.HC2023

CORAE: A Tool for Intuitive and Continuous Retrospective Evaluation of Interactions

Michael J. Sack, Maria Teresa Parreira, Jenny Fu +4

This paper introduces CORAE, a novel web-based open-source tool for COntinuous Retrospective Affect Evaluation, designed to capture continuous affect data about interpersonal perce…

cs.RO2023

Hierarchical Graph Neural Networks for Proprioceptive 6D Pose Estimation of In-hand Objects

Alireza Rezazadeh, Snehal Dikhale, Soshi Iba +1

Robotic manipulation, in particular in-hand object manipulation, often requires an accurate estimate of the object's 6D pose. To improve the accuracy of the estimated pose, state-o…

cs.RO2021★ 9 cited

Deep Tactile Experience: Estimating Tactile Sensor Output from Depth Sensor Data

Karankumar Patel, Soshi Iba, Nawid Jamali

Tactile sensing is inherently contact based. To use tactile data, robots need to make contact with the surface of an object. This is inefficient in applications where an agent need…

cs.RO2021★ 7 cited

VisuoSpatial Foresight for Physical Sequential Fabric Manipulation

Ryan Hoque, Daniel Seita, Ashwin Balakrishna +6

Robotic fabric manipulation has applications in home robotics, textiles, senior care and surgery. Existing fabric manipulation techniques, however, are designed for specific tasks,…

cs.RO2020★ 15 cited

Learning Dense Visual Correspondences in Simulation to Smooth and Fold Real Fabrics

Aditya Ganapathi, Priya Sundaresan, Brijen Thananjeyan +10

Robotic fabric manipulation is challenging due to the infinite dimensional configuration space, self-occlusion, and complex dynamics of fabrics. There has been significant prior wo…

cs.RO2020★ 20 cited

VisuoSpatial Foresight for Multi-Step, Multi-Task Fabric Manipulation

Ryan Hoque, Daniel Seita, Ashwin Balakrishna +6

Robotic fabric manipulation has applications in home robotics, textiles, senior care and surgery. Existing fabric manipulation techniques, however, are designed for specific tasks,…

cs.RO2019★ 9 cited

Deep Imitation Learning of Sequential Fabric Smoothing From an Algorithmic Supervisor

Daniel Seita, Aditya Ganapathi, Ryan Hoque +11

Sequential pulling policies to flatten and smooth fabrics have applications from surgery to manufacturing to home tasks such as bed making and folding clothes. Due to the complexit…

cs.RO2018★ 23 cited

Deep Transfer Learning of Pick Points on Fabric for Robot Bed-Making

Daniel Seita, Nawid Jamali, Michael Laskey +6

A fundamental challenge in manipulating fabric for clothes folding and textiles manufacturing is computing "pick points" to effectively modify the state of an uncertain manifold. W…

cs.RO2017★ 11 cited

Controlled Tactile Exploration and Haptic Object Recognition

Massimo Regoli, Nawid Jamali, Giorgio Metta +1

In this paper we propose a novel method for in-hand object recognition. The method is composed of a grasp stabilization controller and two exploratory behaviours to capture the sha…