no code implementations • 5 Oct 2023 • Mengyu Yang, Patrick Grady, Samarth Brahmbhatt, Arun Balajee Vasudevan, Charles C. Kemp, James Hays
How easy is it to sneak up on a robot?
1 code implementation • 21 Sep 2023 • Jeremy A. Collins, Cody Houff, You Liang Tan, Charles C. Kemp
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).
no code implementations • 5 Jan 2023 • Patrick Grady, Jeremy A. Collins, Chengcheng Tang, Christopher D. Twigg, Kunal Aneja, James Hays, Charles C. Kemp
We present a novel approach that enables diverse data to be captured with only an RGB camera and a cooperative participant.
1 code implementation • 19 Mar 2022 • Patrick Grady, Chengcheng Tang, Samarth Brahmbhatt, Christopher D. Twigg, Chengde Wan, James Hays, Charles C. Kemp
We also show that the output of our model depends on the appearance of the hand and cast shadows near contact regions.
1 code implementation • 20 May 2021 • Henry M. Clever, Patrick Grady, Greg Turk, Charles C. Kemp
We present a method that infers contact pressure between a human body and a mattress from a depth image.
1 code implementation • CVPR 2021 • Patrick Grady, Chengcheng Tang, Christopher D. Twigg, Minh Vo, Samarth Brahmbhatt, Charles C. Kemp
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.
no code implementations • 3 Mar 2021 • Yunbo Zhang, Wenhao Yu, C. Karen Liu, Charles C. Kemp, Greg Turk
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.
no code implementations • 3 Dec 2020 • Tapomayukh Bhattacharjee, Henry M. Clever, Joshua Wade, Charles C. Kemp
We also found that robots can overcome this ambiguity using two temperature sensors with different temperatures prior to contact.
Material Recognition
Robotics
2 code implementations • ECCV 2020 • Samarth Brahmbhatt, Chengcheng Tang, Christopher D. Twigg, Charles C. Kemp, James Hays
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
1 code implementation • 9 Jul 2020 • Zackory Erickson, Yijun Gu, Charles C. Kemp
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.
1 code implementation • 2 Apr 2020 • Zackory Erickson, Eliot Xing, Bharat Srirangam, Sonia Chernova, Charles C. Kemp
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.
1 code implementation • CVPR 2020 • Henry M. Clever, Zackory Erickson, Ariel Kapusta, Greg Turk, C. Karen Liu, Charles C. Kemp
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
4 code implementations • 10 Oct 2019 • Zackory Erickson, Vamsee Gangaram, Ariel Kapusta, C. Karen Liu, Charles C. Kemp
Assistive Gym models a person's physical capabilities and preferences for assistance, which are used to provide a reward function.
no code implementations • 14 Sep 2019 • Alexander Clegg, Zackory Erickson, Patrick Grady, Greg Turk, Charles C. Kemp, C. Karen Liu
We investigated the application of haptic feedback control and deep reinforcement learning (DRL) to robot-assisted dressing.
no code implementations • 17 Jul 2019 • Samarth Brahmbhatt, Charles C. Kemp, James Hays
However, grasp capture - capturing the pose of a hand grasping an object, and orienting it w. r. t.
2 code implementations • CVPR 2019 • Samarth Brahmbhatt, Cusuh Ham, Charles C. Kemp, James Hays
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
2 code implementations • 10 May 2018 • Zackory Erickson, Nathan Luskey, Sonia Chernova, Charles C. Kemp
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.
no code implementations • 21 Apr 2018 • Henry M. Clever, Ariel Kapusta, Daehyung Park, Zackory Erickson, Yash Chitalia, Charles C. Kemp
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.
5 code implementations • 2 Nov 2017 • Daehyung Park, Yuuna Hoshi, Charles C. Kemp
The detection of anomalous executions is valuable for reducing potential hazards in assistive manipulation.
Ranked #2 on
Anomaly Detection
on voraus-AD
no code implementations • 27 Sep 2017 • Zackory Erickson, Henry M. Clever, Greg Turk, C. Karen Liu, Charles C. Kemp
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.
1 code implementation • 10 Jul 2017 • Zackory Erickson, Sonia Chernova, Charles C. Kemp
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.