9 citations · 50 across the 17 of their papers we have counts for
10 papers · 2 filters
ToolFlowNet: Robotic Manipulation with Tools via Predicting Tool Flow from Point Clouds
Daniel Seita, Yufei Wang, Sarthak J. Shetty +3
Point clouds are a widely available and canonical data modality which convey the 3D geometry of a scene. Despite significant progress in classification and segmentation from point…
Learning to Grasp the Ungraspable with Emergent Extrinsic Dexterity
Wenxuan Zhou, David Held
A simple gripper can solve more complex manipulation tasks if it can utilize the external environment such as pushing the object against the table or a vertical wall, known as "Ext…
TAX-Pose: Task-Specific Cross-Pose Estimation for Robot Manipulation
Chuer Pan, Brian Okorn, Harry Zhang +2
How do we imbue robots with the ability to efficiently manipulate unseen objects and transfer relevant skills based on demonstrations? End-to-end learning methods often fail to gen…
Neural Grasp Distance Fields for Robot Manipulation
Thomas Weng, David Held, Franziska Meier +1
We formulate grasp learning as a neural field and present Neural Grasp Distance Fields (NGDF). Here, the input is a 6D pose of a robot end effector and output is a distance to a co…
AutoBag: Learning to Open Plastic Bags and Insert Objects
Lawrence Yunliang Chen, Baiyu Shi, Daniel Seita +4
Thin plastic bags are ubiquitous in retail stores, healthcare, food handling, recycling, homes, and school lunchrooms. They are challenging both for perception (due to specularitie…
Elastic Context: Encoding Elasticity for Data-driven Models of Textiles
Alberta Longhini, Marco Moletta, Alfredo Reichlin +6
Physical interaction with textiles, such as assistive dressing, relies on advanced dextreous capabilities. The underlying complexity in textile behavior when being pulled and stret…