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Dieter Fox
Director
NVIDIA
University of Washington
Latest
DiMSam: Diffusion Models as Samplers for Task and Motion Planning under Partial Observability
Fast Explicit-Input Assistance for Teleoperation in Clutter
Interventional Data Generation for Robust and Data-Efficient Robot Imitation Learning
AutoMate: Specialist and Generalist Assembly Policies over Diverse Geometries
RVT-2: Learning Precise Manipulation from Few Demonstrations
THE COLOSSEUM: A Benchmark for Evaluating Generalization for Robotic Manipulation
URDFormer: A Pipeline for Constructing Articulated Simulation Environments from Real-World Images
Human-In-The-Loop Task and Motion Planning for Imitation Learning
Imitating Task and Motion Planning with Visuomotor Transformers
M2T2: Multi-task Masked Transformer for Object-centric Pick-and-Place
MimicGen: A Data Generation System for Scalable Robot Learning using Human Demonstrations
RVT: Robotic View Transformer for 3D Object Manipulation
STOW: Discrete-Frame Segmentation and Tracking of Unseen Objects for Warehouse Picking Robots
AnyTeleop: A General Vision-Based Dexterous Robot Arm-Hand Teleoperation System
IndustReal: Transferring Contact-Rich Assembly from Simulation to Reality
Sequence-Based Plan Feasibility Prediction for Efficient Task and Motion Planning
CabiNet: Scaling Neural Collision Detection for Object Rearrangement with Procedural Scene Generation
CuRobo: Parellelized Collision-Free Robot Motion Generation
DefGraspNets: Grasp Planning on 3D Fields with Graph Neural Nets
DeXtreme: Transferring Agile In-hand Manipulation from Simulation to Reality
Learning Human-to-Robot Handovers from Point Clouds
Neural 6-DoF Tracking and 3D Reconstruction of Unknown Objects
ProgPrompt: Generating Situated Robot Task Plans using Large Language Models
Bayesian Object Models for Robotic Interaction with Differentiable Probabilistic Programming
Insights towards Sim2Real Contact-Rich Manipulation
Learning Robust Real-World Dexterous Grasping Policies via Implicit Shape Augmentation
MegaPose: 6D Pose Estimationof Novel Objects via Render & Compare
Motion Policy Networks
Neural Geometric Fabrics: Efficiently Learning High-Dimensional Policies from Demonstration
Perceiver-Actor: A Multi-Task Transformer for Robotic Manipulation
Sequence-Based Plan Feasibility Prediction for Efficient Task and Motion Planning
Learning Perceptual Concepts by Bootstrapping from Human Queries
DiSECt: A Differentiable Simulator for Parameter Inference and Control in Robotic Cutting
Correcting Robot Plans with Natural Language Feedback
Factory: Fast Contact for Robotic Assembly
IFOR: Iterative Flow Minimization for Robotic Object Rearrangement
Geometric Fabrics: Generalizing Classical Mechanics to Capture the Physics of Behavior
HandoverSim: A Simulation Framework and Benchmark for Human-to-Robot Object Handovers
Model Predictive Control for Fluid Human-to-Robot Handovers
A Bayesian Treatment of Real-to-Sim for Deformable Object Manipulation
DefGraspSim: Physics-based simulation of grasp outcomes on 3D deformable objects
Assistive Tele-op: Leveraging Transformers to Collect Robotic Task Demonstrations
A Persistent Spatial Semantic Representation for High-level Natural Language Instruction Execution
CLIPort: What and Where Pathways for Robotic Manipulation
Goal-Auxiliary Actor-Critic for 6D Robotic Grasping with Point Clouds
Predicting Stable Configurations for Semantic Placement of Novel Objects
RICE: Refining Instance Masks in Cluttered Environments with Graph Neural Networks
SORNet: Spatial Object-Centric Representations for Sequential Manipulation
STORM: An Integrated Framework for Fast Joint-Space Model-Predictive Control for Reactive Manipulation
Towards Coordinated Robot Motions: End-to-End Learning of Motion Policies on Transform Trees
A differentiable simulator for robotic cutting
DefGraspSim: Simulation-based grasping of 3D deformable objects
DiSeCT: A differentiable simulation engine for autonomous robotic cutting
NeRP: Neural Rearrangement Planning for Unknown Objects
Robust Value Iteration for Continuous Control Tasks.
Value Iteration in Continuous Actions, States and Time.
ACRONYM: A Large-Scale Grasp Dataset Based on Simulation
Alternative Paths Planner (APP) for Provably Fixed-time Manipulation Planning in Semi-structured Environments
Contact-GraspNet: Efficient 6-DoF Grasp Generation in Cluttered Scenes
DexYCB: A Benchmark for Capturing Hand Grasping of Objects
Object Rearrangement Using Learned Implicit Collision Functions
Reactive Human-to-Robot Handovers of Arbitrary Objects
RGB-D Local Implicit Function for Depth Completion of Transparent Objects
Sim-to-Real for Robotic Tactile Sensing via Physics-Based Simulation and Learned Latent Projections
Learning Composable Behavior Embeddings for Long-horizon Visual Navigation
Interpreting and Predicting Tactile Signals for the SynTouch BioTac
Causal Discovery in Physical Systems from Videos.
A User's Guide to Calibrating Robotics Simulators
Learning RGB-D Feature Embeddings for Unseen Object Instance Segmentation
RMPflow: A Geometric Framework for Generation of Multi-Task Motion Policies
Stein Variational Model Predictive Control
STReSSD: Sim-to-Real from Sound for Stochastic Dynamics
Towards Coordinated Robot Motions: End-to-End Learning of Motion Policies on Transform Trees
Collaborative Interaction Models for Optimized Human-Robot Teamwork
Human Grasp Classification for Reactive Human-to-Robot Handovers
Online BayesSim for Combined Simulator Parameter Inference and Policy Improvement
Interpreting and Predicting Tactile Signals via a Physics-Based and Data-Driven Framework
Manipulation Trajectory Optimization with Online Grasp Synthesis and Selection
“Zero-shot” Task Execution through Learning of Pixel-Based Action Preconditions
6-DOF Grasping for Target-driven Object Manipulation in Clutter
Camera-to-Robot Pose Estimation from a Single Image
DexPilot: Depth-Based Teleoperation of Dexterous Robotic Hand-Arm System
Euclideanizing Flows: Diffeomorphic Reduction for Learning Stable Dynamical Systems
Guided Uncertainty-Aware Policy Optimization: Combining Model-Free and Model-Based Strategies for Sample-Efficient Learning
Implicit Reinforcement without Interaction at Scale: Leveraging Large-Scale Robot Manipulation Datasets for Control
In-Hand Object Pose Tracking via Contact Feedback and GPU-Accelerated Robotic Simulation
Inferring the Material Properties of Granular Media for Robotic Tasks
Information Theoretic Model Predictive Q-Learning
LatentFusion: End-to-End Differentiable Reconstruction and Rendering for Unseen Object Pose Estimation
Model-based Generalization under Parameter Uncertainty using Path Integral Control
Motion Reasoning for Goal-Based Imitation Learning
Online Replanning in Belief Space for Partially Observable Task and Motion Problems
Scaling Local Control to Large-Scale Topological Navigation
Self-supervised 6D Object Pose Estimation for Robot Manipulation
Combining Model-Free and Model-Based Strategies for Sample-Efficient Reinforcement Learning
RMPflow: A Computational Graph for Automatic Motion Policy Generation
ContactGrasp: Functional Multi-finger Grasp Synthesis from Contact
Early Fusion for Goal Directed Robotic Vision
Representing Robot Task Plans as Robust Logical-Dynamical Systems
6-DOF GraspNet: Variational Grasp Generation for Object Manipulation
A Billion Ways to Grasp: An Evaluation of Grasp Sampling Schemes on a Dense, Physics-based Grasp Data Set
Conditional Driving from Natural Language Instructions
Learning Reactive Motion Policies in Multiple Task Spaces from Human Demonstrations
The Best of Both Modes: Separately Leveraging RGB and Depth for Unseen Object Instance Segmentation
BayesSim: adaptive domain randomization via probabilistic inference for robotics simulators
PoseRBPF: A Rao-Blackwellized Particle Filter for 6D Object Pose Tracking
Robust Learning of Tactile Force Estimation through Robot Interaction
Deep Object Pose Estimation for Semantic Robotic Grasping of Household Objects
PoseCNN: A Convolutional Neural Network for 6D Object Pose Estimation in Cluttered Scenes
Riemannian Motion Policies
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