49 citations · 120 across the 26 of their papers we have counts for
6 papers · 2 filters
Learning Perceptual Concepts by Bootstrapping from Human Queries
Andreea Bobu, Chris Paxton, Wei Yang +4
When robots operate in human environments, it's critical that humans can quickly teach them new concepts: object-centric properties of the environment that they care about (e.g. ob…
Geometric Fabrics: Generalizing Classical Mechanics to Capture the Physics of Behavior
Karl Van Wyk, Mandy Xie, Anqi Li +9
Classical mechanical systems are central to controller design in energy shaping methods of geometric control. However, their expressivity is limited by position-only metrics and th…
DefGraspSim: Simulation-based grasping of 3D deformable objects
Isabella Huang, Yashraj Narang, Clemens Eppner +4
Robotic grasping of 3D deformable objects (e.g., fruits/vegetables, internal organs, bottles/boxes) is critical for real-world applications such as food processing, robotic surgery…
STORM: An Integrated Framework for Fast Joint-Space Model-Predictive Control for Reactive Manipulation
Mohak Bhardwaj, Balakumar Sundaralingam, Arsalan Mousavian +4
Sampling-based model-predictive control (MPC) is a promising tool for feedback control of robots with complex, non-smooth dynamics, and cost functions. However, the computationally…
Sim-to-Real for Robotic Tactile Sensing via Physics-Based Simulation and Learned Latent Projections
Yashraj Narang, Balakumar Sundaralingam, Miles Macklin +2
Tactile sensing is critical for robotic grasping and manipulation of objects under visual occlusion. However, in contrast to simulations of robot arms and cameras, current simulati…
Interpreting and Predicting Tactile Signals for the SynTouch BioTac
Yashraj S. Narang, Balakumar Sundaralingam, Karl Van Wyk +2
In the human hand, high-density contact information provided by afferent neurons is essential for many human grasping and manipulation capabilities. In contrast, robotic tactile se…