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07/06/2023
Sequential Neural Barriers for Scalable Dynamic Obstacle Avoidance
There are two major challenges for scaling up robot navigation around dy...
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05/17/2023
Smaller Language Models are Better Black-box Machine-Generated Text Detectors
With the advent of fluent generative language models that can produce co...
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04/19/2023
Patching Neural Barrier Functions Using Hamilton-Jacobi Reachability
Learning-based control algorithms have led to major advances in robotics...
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03/03/2023
Learning Stabilization Control from Observations by Learning Lyapunov-like Proxy Models
The deployment of Reinforcement Learning to robotics applications faces ...
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01/20/2023
Accelerating Multi-Agent Planning Using Graph Transformers with Bounded Suboptimality
Conflict-Based Search is one of the most popular methods for multi-agent...
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11/01/2022
Monte Carlo Tree Descent for Black-Box Optimization
The key to Black-Box Optimization is to efficiently search through input...
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10/22/2022
Policy Optimization with Advantage Regularization for Long-Term Fairness in Decision Systems
Long-term fairness is an important factor of consideration in designing ...
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10/17/2022
Learning Control Admissibility Models with Graph Neural Networks for Multi-Agent Navigation
Deep reinforcement learning in continuous domains focuses on learning co...
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10/17/2022
Reducing Collision Checking for Sampling-Based Motion Planning Using Graph Neural Networks
Sampling-based motion planning is a popular approach in robotics for fin...
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10/16/2022
Learning-based Motion Planning in Dynamic Environments Using GNNs and Temporal Encoding
Learning-based methods have shown promising performance for accelerating...
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08/24/2022
SCALE: Online Self-Supervised Lifelong Learning without Prior Knowledge
Unsupervised lifelong learning refers to the ability to learn over time ...
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07/28/2022
Quantifying Safety of Learning-based Self-Driving Control Using Almost-Barrier Functions
Path-tracking control of self-driving vehicles can benefit from deep lea...
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02/23/2022
Safe Control with Learned Certificates: A Survey of Neural Lyapunov, Barrier, and Contraction methods
Learning-enabled control systems have demonstrated impressive empirical ...
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12/16/2021
Learning Bounded Context-Free-Grammar via LSTM and the Transformer:Difference and Explanations
Long Short-Term Memory (LSTM) and Transformers are two popular neural ar...
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09/14/2021
Safe Nonlinear Control Using Robust Neural Lyapunov-Barrier Functions
Safety and stability are common requirements for robotic control systems...
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07/11/2021
Stabilizing Neural Control Using Self-Learned Almost Lyapunov Critics
The lack of stability guarantee restricts the practical use of learning-...
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06/14/2020
Provably Efficient Model-based Policy Adaptation
The high sample complexity of reinforcement learning challenges its use ...
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05/01/2020
Neural Lyapunov Control
We propose new methods for learning control policies and neural network ...
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03/28/2019
How to pick the domain randomization parameters for sim-to-real transfer of reinforcement learning policies?
Recently, reinforcement learning (RL) algorithms have demonstrated remar...
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09/20/2018
Tight Continuous-Time Reachtubes for Lagrangian Reachability
We introduce continuous Lagrangian reachability (CLRT), a new algorithm ...
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07/21/2018
Delta-Decision Procedures for Exists-Forall Problems over the Reals
Solving nonlinear SMT problems over real numbers has wide applications i...
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02/13/2018