Collision avoidance of multi unmanned aerial vehicles: A review

S Huang, RSH Teo, KK Tan - Annual Reviews in Control, 2019‏ - Elsevier
The control of a multiple unmanned aerial vehicle (UAV) system is popular and attracting a
lot of attentions. This is motivated by many practical civil and commercial UAV applications …

[HTML][HTML] Review of conflict resolution methods for manned and unmanned aviation

M Ribeiro, J Ellerbroek, J Hoekstra - Aerospace, 2020‏ - mdpi.com
Current investigations into urban aerial mobility, as well as the continuing growth of global
air transportation, have renewed interest in Conflict Detection and Resolution (CD&R) …

Reluplex: An efficient SMT solver for verifying deep neural networks

G Katz, C Barrett, DL Dill, K Julian… - … Aided Verification: 29th …, 2017‏ - Springer
Deep neural networks have emerged as a widely used and effective means for tackling
complex, real-world problems. However, a major obstacle in applying them to safety-critical …

Efficient formal safety analysis of neural networks

S Wang, K Pei, J Whitehouse… - Advances in neural …, 2018‏ - proceedings.neurips.cc
Neural networks are increasingly deployed in real-world safety-critical domains such as
autonomous driving, aircraft collision avoidance, and malware detection. However, these …

Formal security analysis of neural networks using symbolic intervals

S Wang, K Pei, J Whitehouse, J Yang… - 27th USENIX Security …, 2018‏ - usenix.org
Due to the increasing deployment of Deep Neural Networks (DNNs) in real-world security-
critical domains including autonomous vehicles and collision avoidance systems, formally …

A survey of algorithms for black-box safety validation of cyber-physical systems

A Corso, R Moss, M Koren, R Lee… - Journal of Artificial …, 2021‏ - jair.org
Autonomous cyber-physical systems (CPS) can improve safety and efficiency for safety-
critical applications, but require rigorous testing before deployment. The complexity of these …

A survey on reinforcement learning in aviation applications

P Razzaghi, A Tabrizian, W Guo, S Chen… - … Applications of Artificial …, 2024‏ - Elsevier
Reinforcement learning (RL) has emerged as a powerful tool for addressing complex
decision making problems in various domains, including aviation. This paper provides a …

Considerations for evaluation and generalization in interpretable machine learning

F Doshi-Velez, B Kim - Explainable and interpretable models in computer …, 2018‏ - Springer
As machine learning systems become ubiquitous, there has been a surge of interest in
interpretable machine learning: systems that provide explanation for their outputs. These …

Policy compression for aircraft collision avoidance systems

KD Julian, J Lopez, JS Brush, MP Owen… - 2016 IEEE/AIAA 35th …, 2016‏ - ieeexplore.ieee.org
One approach to designing the decision making logic for an aircraft collision avoidance
system is to frame the problem as Markov decision process and optimize the system using …

Deep neural network compression for aircraft collision avoidance systems

KD Julian, MJ Kochenderfer, MP Owen - Journal of Guidance, Control …, 2019‏ - arc.aiaa.org
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 …