Search Results for author:
Found 21 papers, 13 papers with code
The Un-Kidnappable Robot: Acoustic Localization of Sneaking People
How easy is it to sneak up on a robot?
ForceSight: Text-Guided Mobile Manipulation with Visual-Force Goals
Given a single RGBD image combined with a text prompt, ForceSight determines a target end-effector pose in the camera frame (kinematic goal) and the associated forces (force goal).
PressureVision++: Estimating Fingertip Pressure from Diverse RGB Images
We present a novel approach that enables diverse data to be captured with only an RGB camera and a cooperative participant.
PressureVision: Estimating Hand Pressure from a Single RGB Image
We also show that the output of our model depends on the appearance of the hand and cast shadows near contact regions.
BodyPressure -- Inferring Body Pose and Contact Pressure from a Depth Image
We present a method that infers contact pressure between a human body and a mattress from a depth image.
ContactOpt: Optimizing Contact to Improve Grasps
Given a hand mesh and an object mesh, a deep model trained on ground truth contact data infers desirable contact across the surfaces of the meshes.
Learning to Manipulate Amorphous Materials
We produce a final animation by using inverse kinematics to guide a character's arm and hand to match the motion of the manipulation tool such as a knife or a frying pan.
Material Recognition via Heat Transfer Given Ambiguous Initial Conditions
We also found that robots can overcome this ambiguity using two temperature sensors with different temperatures prior to contact.
Material Recognition
Robotics
ContactPose: A Dataset of Grasps with Object Contact and Hand Pose
We introduce ContactPose, the first dataset of hand-object contact paired with hand pose, object pose, and RGB-D images.
Ranked #1 on
Grasp Contact Prediction
on ContactPose
Assistive VR Gym: Interactions with Real People to Improve Virtual Assistive Robots
Through a formal study with eight participants in AVR Gym, we found that the Original policies performed poorly, the Revised policies performed significantly better, and that improvements to the biomechanical models used to train the Revised policies resulted in simulated people that better match real participants.
Bodies at Rest: 3D Human Pose and Shape Estimation from a Pressure Image using Synthetic Data
We describe a physics-based method that simulates human bodies at rest in a bed with a pressure sensing mat, and present PressurePose, a synthetic dataset with 206K pressure images with 3D human poses and shapes.
3D human pose and shape estimation
3D Human Shape Estimation
+1
Multimodal Material Classification for Robots using Spectroscopy and High Resolution Texture Imaging
Finally, we present how a robot can combine this high resolution local sensing with images from the robot's head-mounted camera to achieve accurate material classification over a scene of objects on a table.
Assistive Gym: A Physics Simulation Framework for Assistive Robotics
Assistive Gym models a person's physical capabilities and preferences for assistance, which are used to provide a reward function.
Learning to Collaborate from Simulation for Robot-Assisted Dressing
We investigated the application of haptic feedback control and deep reinforcement learning (DRL) to robot-assisted dressing.
Towards Markerless Grasp Capture
However, grasp capture - capturing the pose of a hand grasping an object, and orienting it w. r. t.
ContactDB: Analyzing and Predicting Grasp Contact via Thermal Imaging
We present ContactDB, a novel dataset of contact maps for household objects that captures the rich hand-object contact that occurs during grasping, enabled by use of a thermal camera.
Ranked #1 on
Grasp Contact Prediction
on ContactDB
Classification of Household Materials via Spectroscopy
To explore this, we collected a dataset of spectral measurements from two commercially available spectrometers during which a robotic platform interacted with 50 flat material objects, and we show that a neural network model can accurately analyze these measurements.
3D Human Pose Estimation on a Configurable Bed from a Pressure Image
In this work, we present two convolutional neural networks to estimate the 3D joint positions of a person in a configurable bed from a single pressure image.
A Multimodal Anomaly Detector for Robot-Assisted Feeding Using an LSTM-based Variational Autoencoder
The detection of anomalous executions is valuable for reducing potential hazards in assistive manipulation.
Ranked #2 on
Anomaly Detection
on voraus-AD
Deep Haptic Model Predictive Control for Robot-Assisted Dressing
The physical implications of dressing are complicated by non-rigid garments, which can result in a robot indirectly applying high forces to a person's body.
Semi-Supervised Haptic Material Recognition for Robots using Generative Adversarial Networks
Our approach achieves state-of-the-art results and enables a robot to estimate the material class of household objects with ~90% accuracy when 92% of the training data are unlabeled.
