Human Robot Systems (HRS)-reading group
Augmented Reality
Dialog Navigation
Dialog System
- Seamlessly Integrating Factual Information and Social Content with Persuasive Dialogue
- How to Build User Simulators to Train RL-based Dialog Systems
- A Network-based End-to-End Trainable Task-oriented Dialogue System
Human Robot Interaction
- Reimagining RViz: Multidimensional Augmented Reality Robot Signal Design
- Flight, Camera, Action! Using Natural Language and Mixed Reality to Control a Drone
- Explanation Augmented Feedback in Human-in-the-Loop Reinforcement Learning
- Virtual Reality for Robots
- RMM: A Recursive Mental Model for Dialogue Navigation
- Improving Grounded Natural Language Understanding through Human-Robot Dialog
- RoomShift: Room-scale Dynamic Haptics for VR with Furniture-moving Swarm Robots
- That and There: Judging the Intent of Pointing Actions with Robotic Arms
- Communicating Robot Motion Intent with Augmented Reality
Human-Robot Interaction
- DialFRED: Dialogue-Enabled Agents for Embodied Instruction Following
- Descriptive and Prescriptive Visual Guidance to Improve Shared Situational Awareness in Human-Robot Teaming
- Seamlessly Integrating Factual Information and Social Content with Persuasive Dialogue
- Unwinding Rotations Improves User Comfort with Immersive Telepresence Robots
- Outracing champion Gran Turismo drivers with deep reinforcement learning
Knowledge-based Sequential Decision Making
- Visual Semantic Navigation Using Scene Priors
- Continual Learning of Knowledge Graph Embeddings
- Ethically Compliant Sequential Decision Making
- Semantic Linking Maps for Active Visual Object Search
- Commonsense Reasoning and Knowledge Acquisition to Guide Deep Learning on Robots
- Learning Pipelines with Limited Data and Domain Knowledge
Learning
- Transforming a Quadruped into a Guide Robot for the Visually Impaired: Formalizing Wayfinding, Interaction Modeling, and Safety Mechanism
- Neural Volumetric Memory for Visual Locomotion Control
- Legs as Manipulator: Pushing Quadrupedal Agility Beyond Locomotion
- Embodied Amodal Recognition: Learning to Move to Perceive Objects
- MimicPlay: Long-Horizon Imitation Learning by Watching Human Play
- Guiding Pretraining in Reinforcement Learning with Large Language Models
- System Configuration and Navigation of a Guide Dog Robot: Toward Animal Guide Dog-Level Guiding Work
- DM2: Decentralized Multi-Agent Reinforcement Learning for Distribution Matching
- Robotic Guide Dog: Leading a Human with Leash-Guided Hybrid Physical Interaction
- Deep Variational Reinforcement Learning for POMDPs
- Do As I Can, Not As I Say: Grounding Language in Robotic Affordances
- Discovering Generalizable Skills via Automated Generation of Diverse Tasks
- A Reduction of Imitation Learning and Structured Prediction to No-Regret Online Learning
- Continual Learning of Knowledge Graph Embeddings
- Learning When to Quit: Meta-Reasoning for Motion Planning
- Temporal-Logic-Based Reward Shaping for Continuing Reinforcement Learning Tasks
- Joint Inference of Reward Machines and Policies for Reinforcement Learning
- Human-like Planning for Reaching in Cluttered Environments
- Simultaneously Learning Transferable Symbols and Language Groundings from Perceptual Data for Instruction Following
- SAIL: Simulation-Informed Active In-the-Wild Learning
- Improving Grounded Natural Language Understanding through Human-Robot Dialog
- Proximal Policy Optimization Algorithms
- Imagination-Augmented Agents for Deep Reinforcement Learning
- Learning from Interventions using Hierarchical Policies for Safety Learning
- Deep Imitation Learning for Autonomous Driving in Generic Urban Scenarios with Enhanced Safety
- Learning to Teach in Cooperative Multiagent Reinforcement Learning
- Using Natural Language for Reward Shaping in Reinforcement Learning
- Agile Autonomous Driving using End-to-End Deep Imitation Learning
- Adversarial Actor-Critic Method for Task and Motion Planning Problems Using Planning Experience
- Learning Pipelines with Limited Data and Domain Knowledge
- Behavioral Cloning from Observation
Learning and Planning
- Using Commonsense Knowledge to Answer Why-Questions
- Learning Multi-Object Dynamics with Compositional Neural Radiance Fields
- Learning and Deploying Robust Locomotion Policies with Minimal Dynamics Randomization
- Deep Whole-Body Control: Learning a Unified Policy for Manipulation and Locomotion
- Asynchronous Actor-Critic for Multi-Agent Reinforcement Learning
- Detect, Understand, Act: A Neuro-Symbolic Hierarchical Reinforcement Learning Framework (Extended Abstract)∗
- Florence: A New Foundation Model for Computer Vision
- Object Goal Navigation using Goal-Oriented Semantic Exploration
- Learning Feasibility to Imitate Demonstrators with Different Dynamics
- Text-based RL Agents with Commonsense Knowledge: New Challenges, Environments and Baselines
- Reward Machines for Vision-Based Robotic Manipulation
- Decision Transformer: Reinforcement Learning via Sequence Modeling
- Symbolic Knowledge Distillation: from General Language Models to Commonsense Models
- Legged Robots that Keep on Learning: Fine-Tuning Locomotion Policies in the Real World
- ObjectFolder: A Dataset of Objects with Implicit Visual, Auditory, and Tactile Representations
- Galileo: Perceiving Physical Object Properties by Integrating a Physics Engine with Deep Learning
- Advice-Guided Reinforcement Learning in a non-Markovian Environment
- Spatial Intention Maps for Multi-Agent Mobile Manipulation
- What Does BERT with Vision Look At?
- A formal methods approach to interpretable reinforcement learning for robotic planning
Planning
- Human-like Planning for Reaching in Cluttered Environments
- Making Sense of Vision and Touch: Self-Supervised Learning of Multimodal Representations for Contact-Rich Tasks
- Reasoning About Physical Interactions with Object-Oriented Prediction and Planning
- SAIL: Simulation-Informed Active In-the-Wild Learning
- Adversarial Actor-Critic Method for Task and Motion Planning Problems Using Planning Experience
- Behavioral Cloning from Observation
Task-Motion Planning
- Code as Policies: Language Model Programs for Embodied Control
- Using Deep Learning to Bootstrap Abstractions for Hierarchical Robot Planning
- Do As I Can, Not As I Say: Grounding Language in Robotic Affordances
- Pre-Trained Language Models for Interactive Decision-Making
- Language Models as Zero-Shot Planners: Extracting Actionable Knowledge for Embodied Agents
- Online Replanning in Belief Space for Partially Observable Task and Motion Problems
- Elephants Don't Pack Groceries: Robot Task Planning for Low Entropy Belief States
- Planning with Learned Object Importance in Large Problem Instances using Graph Neural Networks
- Learning When to Quit: Meta-Reasoning for Motion Planning
- Hierarchical Planning for Long-Horizon Manipulation with Geometric and Symbolic Scene Graphs
- Making Sense of Vision and Touch: Self-Supervised Learning of Multimodal Representations for Contact-Rich Tasks