Search Results for author: Kyle D. Julian

Found 6 papers, 3 papers with code

Generating Probabilistic Safety Guarantees for Neural Network Controllers

1 code implementation1 Mar 2021 Sydney M. Katz, Kyle D. Julian, Christopher A. Strong, Mykel J. Kochenderfer

In this work, we develop a method to use the results from neural network verification tools to provide probabilistic safety guarantees on a neural network controller.

Collision Avoidance

Global Optimization of Objective Functions Represented by ReLU Networks

no code implementations7 Oct 2020 Christopher A. Strong, Haoze Wu, Aleksandar Zeljić, Kyle D. Julian, Guy Katz, Clark Barrett, Mykel J. Kochenderfer

However, individual "yes or no" questions cannot answer qualitative questions such as "what is the largest error within these bounds"; the answers to these lie in the domain of optimization.

Guaranteeing Safety for Neural Network-Based Aircraft Collision Avoidance Systems

1 code implementation15 Dec 2019 Kyle D. Julian, Mykel J. Kochenderfer

The neural network outputs are bounded using neural network verification tools like Reluplex and Reluval, and a reachability method determines all possible ways aircraft encounters will resolve using neural network advisories and assuming bounded aircraft dynamics.

Collision Avoidance

Deep Neural Network Compression for Aircraft Collision Avoidance Systems

no code implementations9 Oct 2018 Kyle D. Julian, Mykel J. Kochenderfer, Michael P. Owen

One approach to designing decision making logic for an aircraft collision avoidance system frames the problem as a Markov decision process and optimizes the system using dynamic programming.

Collision Avoidance Decision Making +1

Image-based Guidance of Autonomous Aircraft for Wildfire Surveillance and Prediction

1 code implementation4 Oct 2018 Kyle D. Julian, Mykel J. Kochenderfer

The second approach uses a particle filter to predict wildfire growth and uses observations to estimate uncertainties relating to wildfire expansion.


Cannot find the paper you are looking for? You can Submit a new open access paper.