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08/11/2023
A Game-Theoretic Framework for Joint Forecasting and Planning
Planning safe robot motions in the presence of humans requires reliable ...
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05/26/2023
Demo2Code: From Summarizing Demonstrations to Synthesizing Code via Extended Chain-of-Thought
Language instructions and demonstrations are two natural ways for users ...
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03/26/2023
Inverse Reinforcement Learning without Reinforcement Learning
Inverse Reinforcement Learning (IRL) is a powerful set of techniques for...
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03/01/2023
The Virtues of Laziness in Model-based RL: A Unified Objective and Algorithms
We propose a novel approach to addressing two fundamental challenges in ...
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08/19/2022
Game-Theoretic Algorithms for Conditional Moment Matching
A variety of problems in econometrics and machine learning, including in...
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08/03/2022
Sequence Model Imitation Learning with Unobserved Contexts
We consider imitation learning problems where the expert has access to a...
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05/30/2022
Minimax Optimal Online Imitation Learning via Replay Estimation
Online imitation learning is the problem of how best to mimic expert dem...
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02/02/2022
Causal Imitation Learning under Temporally Correlated Noise
We develop algorithms for imitation learning from policy data that was c...
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10/05/2021
A Critique of Strictly Batch Imitation Learning
Recent work by Jarrett et al. attempts to frame the problem of offline i...
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04/11/2021
Guided Incremental Local Densification for Accelerated Sampling-based Motion Planning
Sampling-based motion planners rely on incremental densification to disc...
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04/02/2021
Learning Online from Corrective Feedback: A Meta-Algorithm for Robotics
A key challenge in Imitation Learning (IL) is that optimal state actions...
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03/04/2021
Of Moments and Matching: Trade-offs and Treatments in Imitation Learning
We provide a unifying view of a large family of previous imitation learn...
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02/04/2021
Feedback in Imitation Learning: The Three Regimes of Covariate Shift
Imitation learning practitioners have often noted that conditioning poli...
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12/10/2020
Blending MPC Value Function Approximation for Efficient Reinforcement Learning
Model-Predictive Control (MPC) is a powerful tool for controlling comple...
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02/27/2020
Posterior Sampling for Anytime Motion Planning on Graphs with Expensive-to-Evaluate Edges
Collision checking is a computational bottleneck in motion planning, req...
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02/07/2020
Bayesian Residual Policy Optimization: Scalable Bayesian Reinforcement Learning with Clairvoyant Experts
Informed and robust decision making in the face of uncertainty is critic...
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10/15/2019
Autonomous Aerial Cinematography In Unstructured Environments With Learned Artistic Decision-Making
Aerial cinematography is revolutionizing industries that require live an...
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08/21/2019
MuSHR: A Low-Cost, Open-Source Robotic Racecar for Education and Research
We present MuSHR, the Multi-agent System for non-Holonomic Racing. MuSHR...
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07/22/2019
LEGO: Leveraging Experience in Roadmap Generation for Sampling-Based Planning
We consider the problem of leveraging prior experience to generate roadm...
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07/16/2019
Leveraging Experience in Lazy Search
Lazy graph search algorithms are efficient at solving motion planning pr...
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05/30/2019
Imitation Learning as f-Divergence Minimization
We address the problem of imitation learning with multi-modal demonstrat...
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04/04/2019
Generalized Lazy Search for Robot Motion Planning: Interleaving Search and Edge Evaluation via Event-based Toggles
Lazy search algorithms can efficiently solve problems where edge evaluat...
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04/04/2019
Towards a Robust Aerial Cinematography Platform: Localizing and Tracking Moving Targets in Unstructured Environments
The use of drones for aerial cinematography has revolutionized several a...
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10/06/2018
Bayes-CPACE: PAC Optimal Exploration in Continuous Space Bayes-Adaptive Markov Decision Processes
We present the first PAC optimal algorithm for Bayes-Adaptive Markov Dec...
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08/28/2018
Autonomous drone cinematographer: Using artistic principles to create smooth, safe, occlusion-free trajectories for aerial filming
Autonomous aerial cinematography has the potential to enable automatic c...
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04/07/2018
Hindsight is Only 50/50: Unsuitability of MDP based Approximate POMDP Solvers for Multi-resolution Information Gathering
Partially Observable Markov Decision Processes (POMDPs) offer an elegant...
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11/20/2017
Bayesian Active Edge Evaluation on Expensive Graphs
Robots operate in environments with varying implicit structure. For inst...
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11/17/2017
Data-driven Planning via Imitation Learning
Robot planning is the process of selecting a sequence of actions that op...
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11/10/2017
Anytime Motion Planning on Large Dense Roadmaps with Expensive Edge Evaluations
We propose an algorithmic framework for efficient anytime motion plannin...
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07/10/2017
Learning Heuristic Search via Imitation
Robotic motion planning problems are typically solved by constructing a ...
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11/13/2016