Michael Everett | DeepAI

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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...

0 Anthony Francis, et al. ∙

∙ 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...

0 Michael Everett, et al. ∙

∙ 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...

0 Nicholas Rober, et al. ∙

∙ 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...

0 Lakshay Sharma, et al. ∙

∙ 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 ...

0 Xiaoyi Cai, et al. ∙

∙ 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...

0 Nicholas Rober, et al. ∙

∙ 04/14/2022

Backward Reachability Analysis for Neural Feedback Loops

The increasing prevalence of neural networks (NNs) in safety-critical ap...

0 Nicholas Rober, et al. ∙

∙ 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...

0 Xiaoyi Cai, et al. ∙

∙ 03/07/2022

Influencing Long-Term Behavior in Multiagent Reinforcement Learning

The main challenge of multiagent reinforcement learning is the difficult...

0 Dong-Ki Kim, et al. ∙

∙ 09/30/2021

Neural Network Verification in Control

Learning-based methods could provide solutions to many of the long-stand...

0 Michael Everett, et al. ∙

∙ 09/21/2021

Demonstration-Efficient Guided Policy Search via Imitation of Robust Tube MPC

We propose a demonstration-efficient strategy to compress a computationa...

0 Andrea Tagliabue, et al. ∙

∙ 08/09/2021

Reachability Analysis of Neural Feedback Loops

Neural Networks (NNs) can provide major empirical performance improvemen...

0 Michael Everett, et al. ∙

∙ 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...

0 Bruno Brito, et al. ∙

∙ 01/05/2021

Efficient Reachability Analysis of Closed-Loop Systems with Neural Network Controllers

Neural Networks (NNs) can provide major empirical performance improvemen...

0 Michael Everett, et al. ∙

∙ 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...

0 Michael Everett, et al. ∙

∙ 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...

1 Rose E. Wang, et al. ∙

∙ 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 ...

0 Samaneh Hosseini Semnani, et al. ∙

∙ 01/09/2020

FASTER: Fast and Safe Trajectory Planner for Flights in Unknown Environments

Planning high-speed trajectories for UAVs in unknown environments requir...

27 Jesus Tordesillas, et al. ∙

∙ 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...

0 Björn Lütjens, et al. ∙

∙ 10/24/2019

Collision Avoidance in Pedestrian-Rich Environments with Deep Reinforcement Learning

Collision avoidance algorithms are essential for safe and efficient robo...

20 Michael Everett, et al. ∙

∙ 08/24/2019

Planning Beyond the Sensing Horizon Using a Learned Context

Last-mile delivery systems commonly propose the use of autonomous roboti...

6 Michael Everett, et al. ∙

∙ 10/19/2018

Safe Reinforcement Learning with Model Uncertainty Estimates

Many current autonomous systems are being designed with a strong relianc...

0 Björn Lütjens, et al. ∙

∙ 05/04/2018

Motion Planning Among Dynamic, Decision-Making Agents with Deep Reinforcement Learning

Robots that navigate among pedestrians use collision avoidance algorithm...

2 Michael Everett, et al. ∙

∙ 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...

0 Shayegan Omidshafiei, et al. ∙

∙ 03/16/2017

Semantic-level Decentralized Multi-Robot Decision-Making using Probabilistic Macro-Observations

Robust environment perception is essential for decision-making on robots...

0 Shayegan Omidshafiei, et al. ∙

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