research
∙
09/21/2023
TeachingBot: Robot Teacher for Human Handwriting
Teaching physical skills to humans requires one-on-one interaction betwe...
share
research
∙
07/21/2023
How to Tidy Up a Table: Fusing Visual and Semantic Commonsense Reasoning for Robotic Tasks with Vague Objectives
Vague objectives in many real-life scenarios pose long-standing challeng...
research
∙
07/13/2023
On the Effective Horizon of Inverse Reinforcement Learning
Inverse reinforcement learning (IRL) algorithms often rely on (forward) ...
research
∙
06/27/2023
What Truly Matters in Trajectory Prediction for Autonomous Driving?
In the autonomous driving system, trajectory prediction plays a vital ro...
research
∙
05/23/2023
Large Language Models as Commonsense Knowledge for Large-Scale Task Planning
Natural language provides a natural interface for human communication, y...
research
∙
03/12/2023
The Planner Optimization Problem: Formulations and Frameworks
Identifying internal parameters for planning is crucial to maximizing th...
research
∙
02/13/2023
COACH: Cooperative Robot Teaching
Knowledge and skills can transfer from human teachers to human students....
research
∙
10/24/2022
Benchmarking Deformable Object Manipulation with Differentiable Physics
Deformable Object Manipulation (DOM) is of significant importance to bot...
research
∙
10/01/2022
Differentiable Parsing and Visual Grounding of Verbal Instructions for Object Placement
Grounding spatial relations in natural language for object placing could...
research
∙
09/23/2022
LEADER: Learning Attention over Driving Behaviors for Planning under Uncertainty
Uncertainty on human behaviors poses a significant challenge to autonomo...
research
∙
09/21/2022
Partially Observable Markov Decision Processes in Robotics: A Survey
Noisy sensing, imperfect control, and environment changes are defining c...
research
∙
06/09/2022
Receding Horizon Inverse Reinforcement Learning
Inverse reinforcement learning (IRL) seeks to infer a cost function that...
research
∙
02/25/2022
Context-Hierarchy Inverse Reinforcement Learning
An inverse reinforcement learning (IRL) agent learns to act intelligentl...
research
∙
09/16/2021
End-to-End Partially Observable Visual Navigation in a Diverse Environment
How can a robot navigate successfully in a rich and diverse environment,...
research
∙
08/25/2021
INVIGORATE: Interactive Visual Grounding and Grasping in Clutter
This paper presents INVIGORATE, a robot system that interacts with human...
research
∙
07/19/2021
Ab Initio Particle-based Object Manipulation
This paper presents Particle-based Object Manipulation (Prompt), a new a...
research
∙
05/17/2021
Differentiable SLAM-net: Learning Particle SLAM for Visual Navigation
Simultaneous localization and mapping (SLAM) remains challenging for a n...
research
∙
04/25/2021
Learning Latent Graph Dynamics for Deformable Object Manipulation
Manipulating deformable objects, such as cloth and ropes, is a long-stan...
research
∙
01/11/2021
Closing the Planning-Learning Loop with Application to Autonomous Driving in a Crowd
Imagine an autonomous robot vehicle driving in dense, possibly unregulat...
research
∙
11/11/2020
Simulating Autonomous Driving in Massive Mixed Urban Traffic
Autonomous driving in an unregulated urban crowd is an outstanding chall...
research
∙
11/07/2020
MAGIC: Learning Macro-Actions for Online POMDP Planning using Generator-Critic
When robots operate in the real-world, they need to handle uncertainties...
research
∙
08/06/2020
Contrastive Variational Model-Based Reinforcement Learning for Complex Observations
Deep model-based reinforcement learning (MBRL) has achieved great sample...
research
∙
07/13/2020
DinerDash Gym: A Benchmark for Policy Learning in High-Dimensional Action Space
It has been arduous to assess the progress of a policy learning algorith...
research
∙
02/23/2020
Discriminative Particle Filter Reinforcement Learning for Complex Partial Observations
Deep reinforcement learning is successful in decision making for sophist...
research
∙
11/11/2019
SUMMIT: A Simulator for Urban Driving in Massive Mixed Traffic
Autonomous driving in an unregulated urban crowd is an outstanding chall...
research
∙
09/03/2019
Robot Capability and Intention in Trust-based Decisions across Tasks
In this paper, we present results from a human-subject study designed to...
research
∙
05/30/2019
Particle Filter Recurrent Neural Networks
Recurrent neural networks (RNNs) have been extraordinarily successful fo...
research
∙
05/29/2019
LeTS-Drive: Driving in a Crowd by Learning from Tree Search
Autonomous driving in a crowded environment, e.g., a busy traffic inters...
research
∙
05/28/2019
Differentiable Algorithm Networks for Composable Robot Learning
This paper introduces the Differentiable Algorithm Network (DAN), a comp...
research
∙
12/11/2018
Guided Exploration of Human Intentions for Human-Robot Interaction
Robot understanding of human intentions is essential for fluid human-rob...
research
∙
07/17/2018
Integrating Algorithmic Planning and Deep Learning for Partially Observable Navigation
We propose to take a novel approach to robot system design where each bu...
research
∙
07/05/2018
The Transfer of Human Trust in Robot Capabilities across Tasks
Trust is crucial in shaping human interactions with one another and with...
research
∙
06/11/2018
Interactive Visual Grounding of Referring Expressions for Human-Robot Interaction
This paper presents INGRESS, a robot system that follows human natural l...
research
∙
05/30/2018
PORCA: Modeling and Planning for Autonomous Driving among Many Pedestrians
This paper presents a planning system for autonomous driving among many ...
research
∙
05/30/2018
Autonomous Driving among Many Pedestrians: Models and Algorithms
Driving among a dense crowd of pedestrians is a major challenge for auto...
research
∙
05/23/2018
Particle Filter Networks with Application to Visual Localization
Particle filtering is a powerful method for sequential state estimation ...
research
∙
05/23/2018
Particle Filter Networks: End-to-End Probabilistic Localization From Visual Observations
Particle filters sequentially approximate posterior distributions by sam...
research
∙
02/17/2018
HyP-DESPOT: A Hybrid Parallel Algorithm for Online Planning under Uncertainty
Planning under uncertainty is critical for robust robot performance in u...
research
∙
01/12/2018
Planning with Trust for Human-Robot Collaboration
Trust is essential for human-robot collaboration and user adoption of au...
research
∙
10/16/2017
Intention-Net: Integrating Planning and Deep Learning for Goal-Directed Autonomous Navigation
How can a delivery robot navigate reliably to a destination in a new off...
research
∙
07/18/2017
Grounding Spatio-Semantic Referring Expressions for Human-Robot Interaction
The human language is one of the most natural interfaces for humans to i...
research
∙
03/20/2017
QMDP-Net: Deep Learning for Planning under Partial Observability
This paper introduces the QMDP-net, a neural network architecture for pl...
research
∙
12/06/2016
Factored Contextual Policy Search with Bayesian Optimization
Scarce data is a major challenge to scaling robot learning to truly comp...
research
∙
09/12/2016
DESPOT: Online POMDP Planning with Regularization
The partially observable Markov decision process (POMDP) provides a prin...
research
∙
02/16/2016
POMDP-lite for Robust Robot Planning under Uncertainty
The partially observable Markov decision process (POMDP) provides a prin...
research
∙
06/27/2012