59 citations · 225 across the 39 of their papers we have counts for
7 papers · 2 filters
Gaussian Process Constraint Learning for Scalable Chance-Constrained Motion Planning from Demonstrations
Glen Chou, Hao Wang, Dmitry Berenson
We propose a method for learning constraints represented as Gaussian processes (GPs) from locally-optimal demonstrations. Our approach uses the Karush-Kuhn-Tucker (KKT) optimality…
CLASP: Constrained Latent Shape Projection for Refining Object Shape from Robot Contact
Brad Saund, Dmitry Berenson
Robots need both visual and contact sensing to effectively estimate the state of their environment. Camera RGBD data provides rich information of the objects surrounding the robot,…
Challenges and Outlook in Robotic Manipulation of Deformable Objects
Jihong Zhu, Andrea Cherubini, Claire Dune +10
Deformable object manipulation (DOM) is an emerging research problem in robotics. The ability to manipulate deformable objects endows robots with higher autonomy and promises new a…
Model Error Propagation via Learned Contraction Metrics for Safe Feedback Motion Planning of Unknown Systems
Glen Chou, Necmiye Ozay, Dmitry Berenson
We present a method for contraction-based feedback motion planning of locally incrementally exponentially stabilizable systems with unknown dynamics that provides probabilistic saf…
Fusing RGBD Tracking and Segmentation Tree Sampling for Multi-Hypothesis Volumetric Segmentation
Andrew Price, Kun Huang, Dmitry Berenson
Despite rapid progress in scene segmentation in recent years, 3D segmentation methods are still limited when there is severe occlusion. The key challenge is estimating the segment…
Keep it Simple: Data-efficient Learning for Controlling Complex Systems with Simple Models
Thomas Power, Dmitry Berenson
When manipulating a novel object with complex dynamics, a state representation is not always available, for example for deformable objects. Learning both a representation and dynam…
Occlusion-robust Deformable Object Tracking without Physics Simulation
Cheng Chi, Dmitry Berenson
Estimating the state of a deformable object is crucial for robotic manipulation, yet accurate tracking is challenging when the object is partially-occluded. To address this problem…