59 citations · 225 across the 39 of their papers we have counts for
40 papers · 1 filter
PDDL-ART: Autonomous Symbolic Abstraction From Demonstration For Long-Horizon Robotic Manipulation Using Vision-Language Models
Disha Kamale, Dmitry Berenson
Symbolic planning with PDDL offers a principled framework for long-horizon robot manipulation, but constructing accurate PDDL domain and problem descriptions remains a significant…
STEMbot: A Compliant Robot for Under-Canopy Plant Navigation
Zachary Charlick, Nilay Roy Choudhury, Haoyu Ma +2
The scalability of organic agriculture is partially limited by the labor costs associated with monitoring for pests. While drones and rovers are well-suited for agricultural monito…
Motion Planning as Online Learning: A Multi-Armed Bandit Approach to Kinodynamic Sampling-Based Planning
Marco Faroni, Dmitry Berenson
Kinodynamic motion planners allow robots to perform complex manipulation tasks under dynamics constraints or with black-box models. However, they struggle to find high-quality solu…
Constrained Stein Variational Trajectory Optimization
Thomas Power, Dmitry Berenson
We present Constrained Stein Variational Trajectory Optimization (CSVTO), an algorithm for performing trajectory optimization with constraints on a set of trajectories in parallel.…
Integrated Object Deformation and Contact Patch Estimation from Visuo-Tactile Feedback
Mark Van der Merwe, Youngsun Wi, Dmitry Berenson +1
Reasoning over the interplay between object deformation and force transmission through contact is central to the manipulation of compliant objects. In this paper, we propose Neural…
CHSEL: Producing Diverse Plausible Pose Estimates from Contact and Free Space Data
Sheng Zhong, Nima Fazeli, Dmitry Berenson
This paper proposes a novel method for estimating the set of plausible poses of a rigid object from a set of points with volumetric information, such as whether each point is in fr…
Learning the Dynamics of Compliant Tool-Environment Interaction for Visuo-Tactile Contact Servoing
Mark Van der Merwe, Dmitry Berenson, Nima Fazeli
Many manipulation tasks require the robot to control the contact between a grasped compliant tool and the environment, e.g. scraping a frying pan with a spatula. However, modeling…
Manipulation via Membranes: High-Resolution and Highly Deformable Tactile Sensing and Control
Miquel Oller, Mireia Planas, Dmitry Berenson +1
Collocated tactile sensing is a fundamental enabling technology for dexterous manipulation. However, deformable sensors introduce complex dynamics between the robot, grasped object…
Focused Adaptation of Dynamics Models for Deformable Object Manipulation
Peter Mitrano, Alex LaGrassa, Oliver Kroemer +1
In order to efficiently learn a dynamics model for a task in a new environment, one can adapt a model learned in a similar source environment. However, existing adaptation methods…
Safe Output Feedback Motion Planning from Images via Learned Perception Modules and Contraction Theory
Glen Chou, Necmiye Ozay, Dmitry Berenson
We present a motion planning algorithm for a class of uncertain control-affine nonlinear systems which guarantees runtime safety and goal reachability when using high-dimensional s…
Variational Inference MPC using Normalizing Flows and Out-of-Distribution Projection
Thomas Power, Dmitry Berenson
We propose a Model Predictive Control (MPC) method for collision-free navigation that uses amortized variational inference to approximate the distribution of optimal control sequen…
Data Augmentation for Manipulation
Peter Mitrano, Dmitry Berenson
The success of deep learning depends heavily on the availability of large datasets, but in robotic manipulation there are many learning problems for which such datasets do not exis…
Soft Tracking Using Contacts for Cluttered Objects to Perform Blind Object Retrieval
Sheng Zhong, Nima Fazeli, Dmitry Berenson
Retrieving an object from cluttered spaces suchas cupboards, refrigerators, or bins requires tracking objects with limited or no visual sensing. In these scenarios, contact feedbac…
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…
Diverse Plausible Shape Completions from Ambiguous Depth Images
Brad Saund, Dmitry Berenson
We propose PSSNet, a network architecture for generating diverse plausible 3D reconstructions from a single 2.5D depth image. Existing methods tend to produce only small variations…
Uncertainty-Aware Constraint Learning for Adaptive Safe Motion Planning from Demonstrations
Glen Chou, Necmiye Ozay, Dmitry Berenson
We present a method for learning to satisfy uncertain constraints from demonstrations. Our method uses robust optimization to obtain a belief over the potentially infinite set of p…
Tracking Partially-Occluded Deformable Objects while Enforcing Geometric Constraints
Yixuan Wang, Dale McConachie, Dmitry Berenson
In order to manipulate a deformable object, such as rope or cloth, in unstructured environments, robots need a way to estimate its current shape. However, tracking the shape of a d…
TAMPC: A Controller for Escaping Traps in Novel Environments
Sheng Zhong, Zhenyuan Zhang, Nima Fazeli +1
We propose an approach to online model adaptation and control in the challenging case of hybrid and discontinuous dynamics where actions may lead to difficult-to-escape "trap" stat…