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09/03/2023
Learning-Aware Safety for Interactive Autonomy
One of the outstanding challenges for the widespread deployment of robot...
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07/01/2023
Fast, Smooth, and Safe: Implicit Control Barrier Functions through Reach-Avoid Differential Dynamic Programming
Safety is a central requirement for autonomous system operation across d...
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02/01/2023
Active Uncertainty Reduction for Safe and Efficient Interaction Planning: A Shielding-Aware Dual Control Approach
The ability to accurately predict the opponent's behavior is central to ...
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02/15/2022
Active Uncertainty Learning for Human-Robot Interaction: An Implicit Dual Control Approach
Predictive models are effective in reasoning about human motion, a cruci...
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01/20/2022
Sim-to-Lab-to-Real: Safe Reinforcement Learning with Shielding and Generalization Guarantees
Safety is a critical component of autonomous systems and remains a chall...
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12/23/2021
Safety and Liveness Guarantees through Reach-Avoid Reinforcement Learning
Reach-avoid optimal control problems, in which the system must reach cer...
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12/22/2021
ProBF: Learning Probabilistic Safety Certificates with Barrier Functions
Safety-critical applications require controllers/policies that can guara...
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10/02/2021
SHARP: Shielding-Aware Robust Planning for Safe and Efficient Human-Robot Interaction
Jointly achieving safety and efficiency in human-robot interaction (HRI)...
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09/16/2021
Back to the Future: Efficient, Time-Consistent Solutions in Reach-Avoid Games
We study the class of reach-avoid dynamic games in which multiple agents...
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05/17/2021
Safe Occlusion-aware Autonomous Driving via Game-Theoretic Active Perception
Autonomous vehicles interacting with other traffic participants heavily ...
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02/14/2021
FaSTrack: a Modular Framework for Real-Time Motion Planning and Guaranteed Safe Tracking
Real-time, guaranteed safe trajectory planning is vital for navigation i...
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02/03/2020
Quantifying Hypothesis Space Misspecification in Learning from Human-Robot Demonstrations and Physical Corrections
Human input has enabled autonomous systems to improve their capabilities...
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01/13/2020
LESS is More: Rethinking Probabilistic Models of Human Behavior
Robots need models of human behavior for both inferring human goals and ...
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11/19/2018
Safe and Complete Real-Time Planning and Exploration in Unknown Environments
We present a new framework for motion planning that wraps around existin...
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11/14/2018
A Scalable Framework For Real-Time Multi-Robot, Multi-Human Collision Avoidance
Robust motion planning is a well-studied problem in the robotics literat...
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10/13/2018
Hierarchical Game-Theoretic Planning for Autonomous Vehicles
The actions of an autonomous vehicle on the road affect and are affected...
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10/11/2018
Learning under Misspecified Objective Spaces
Learning robot objective functions from human input has become increasin...
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09/03/2018
A Minimum Discounted Reward Hamilton-Jacobi Formulation for Computing Reachable Sets
We propose a novel formulation for approximating reachable sets through ...
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06/11/2018
An Efficient, Generalized Bellman Update For Cooperative Inverse Reinforcement Learning
Our goal is for AI systems to correctly identify and act according to th...
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05/31/2018
Probabilistically Safe Robot Planning with Confidence-Based Human Predictions
In order to safely operate around humans, robots can employ predictive m...
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02/14/2018
Generating Plans that Predict Themselves
Collaboration requires coordination, and we coordinate by anticipating o...
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02/06/2018
Goal Inference Improves Objective and Perceived Performance in Human-Robot Collaboration
The study of human-robot interaction is fundamental to the design and us...
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10/12/2017
Planning, Fast and Slow: A Framework for Adaptive Real-Time Safe Trajectory Planning
Motion planning is an extremely well-studied problem in the robotics com...
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07/20/2017
