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06/29/2023
Principles and Guidelines for Evaluating Social Robot Navigation Algorithms
A major challenge to deploying robots widely is navigation in human-popu...
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12/09/2022
DRIP: Domain Refinement Iteration with Polytopes for Backward Reachability Analysis of Neural Feedback Loops
Safety certification of data-driven control techniques remains a major o...
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10/14/2022
A Hybrid Partitioning Strategy for Backward Reachability of Neural Feedback Loops
As neural networks become more integrated into the systems that we depen...
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10/12/2022
RAMP: A Risk-Aware Mapping and Planning Pipeline for Fast Off-Road Ground Robot Navigation
A key challenge in fast ground robot navigation in 3D terrain is balanci...
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10/01/2022
Probabilistic Traversability Model for Risk-Aware Motion Planning in Off-Road Environments
A key challenge in off-road navigation is that even visually similar or ...
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09/28/2022
Backward Reachability Analysis of Neural Feedback Loops: Techniques for Linear and Nonlinear Systems
The increasing prevalence of neural networks (NNs) in safety-critical ap...
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04/14/2022
Backward Reachability Analysis for Neural Feedback Loops
The increasing prevalence of neural networks (NNs) in safety-critical ap...
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03/25/2022
Risk-Aware Off-Road Navigation via a Learned Speed Distribution Map
Motion planning in off-road environments requires reasoning about both t...
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03/07/2022
Influencing Long-Term Behavior in Multiagent Reinforcement Learning
The main challenge of multiagent reinforcement learning is the difficult...
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09/30/2021
Neural Network Verification in Control
Learning-based methods could provide solutions to many of the long-stand...
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09/21/2021
Demonstration-Efficient Guided Policy Search via Imitation of Robust Tube MPC
We propose a demonstration-efficient strategy to compress a computationa...
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08/09/2021
Reachability Analysis of Neural Feedback Loops
Neural Networks (NNs) can provide major empirical performance improvemen...
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02/25/2021
Where to go next: Learning a Subgoal Recommendation Policy for Navigation Among Pedestrians
Robotic navigation in environments shared with other robots or humans re...
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01/05/2021
Efficient Reachability Analysis of Closed-Loop Systems with Neural Network Controllers
Neural Networks (NNs) can provide major empirical performance improvemen...
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10/01/2020
Robustness Analysis of Neural Networks via Efficient Partitioning: Theory and Applications in Control Systems
Neural networks (NNs) are now routinely implemented on systems that must...
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02/16/2020
R-MADDPG for Partially Observable Environments and Limited Communication
There are several real-world tasks that would ben-efit from applying mul...
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01/18/2020
Multi-agent Motion Planning for Dense and Dynamic Environments via Deep Reinforcement Learning
This paper introduces a hybrid algorithm of deep reinforcement learning ...
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01/09/2020
FASTER: Fast and Safe Trajectory Planner for Flights in Unknown Environments
Planning high-speed trajectories for UAVs in unknown environments requir...
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10/28/2019
Certified Adversarial Robustness for Deep Reinforcement Learning
Deep Neural Network-based systems are now the state-of-the-art in many r...
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10/24/2019
Collision Avoidance in Pedestrian-Rich Environments with Deep Reinforcement Learning
Collision avoidance algorithms are essential for safe and efficient robo...
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08/24/2019
Planning Beyond the Sensing Horizon Using a Learned Context
Last-mile delivery systems commonly propose the use of autonomous roboti...
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10/19/2018
Safe Reinforcement Learning with Model Uncertainty Estimates
Many current autonomous systems are being designed with a strong relianc...
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05/04/2018
Motion Planning Among Dynamic, Decision-Making Agents with Deep Reinforcement Learning
Robots that navigate among pedestrians use collision avoidance algorithm...
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03/16/2017
Scalable Accelerated Decentralized Multi-Robot Policy Search in Continuous Observation Spaces
This paper presents the first ever approach for solving continuous-obser...
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03/16/2017