Real-time adaptive entry trajectory generation with modular policy and deep reinforcement learning
Recently, data-driven entry trajectory generation algorithms of hypersonic vehicles were
highlighted for their high accuracy with low computational costs. Learning a unique black …
highlighted for their high accuracy with low computational costs. Learning a unique black …
Anti-interception guidance for hypersonic glide vehicle: a deep reinforcement learning approach
L Jiang, Y Nan, Y Zhang, Z Li - Aerospace, 2022 - mdpi.com
Anti-interception guidance can enhance a hypersonic glide vehicle (HGV) compard to
multiple interceptors. In general, anti-interception guidance for aircraft can be divided into …
multiple interceptors. In general, anti-interception guidance for aircraft can be divided into …
A hierarchical reinforcement learning method for missile evasion and guidance
M Yan, R Yang, Y Zhang, L Yue, D Hu - Scientific Reports, 2022 - nature.com
This paper proposes an algorithm for missile manoeuvring based on a hierarchical proximal
policy optimization (PPO) reinforcement learning algorithm, which enables a missile to guide …
policy optimization (PPO) reinforcement learning algorithm, which enables a missile to guide …
Deep Reinforcement Learning for Weapons to Targets Assignment in a Hypersonic strike
We use deep reinforcement learning (RL) to optimize a weapons to target assignment (WTA)
policy for multi-vehicle hypersonic strike against multiple targets. The objective is to …
policy for multi-vehicle hypersonic strike against multiple targets. The objective is to …
Integrated and adaptive guidance and control for endoatmospheric missiles via reinforcement learning
We apply a reinforcement meta-learning framework to optimize an integrated and adaptive
guidance and flight control system for an air-to-air missile. The system is implemented as a …
guidance and flight control system for an air-to-air missile. The system is implemented as a …
Trajectory optimization of a subsonic unpowered gliding vehicle using control vector parameterization
In many aero gliding vehicles, achieving the maximum gliding range is a challenging task. A
frequent example is the breakdown of an engine during flight or the use of unpowered stand …
frequent example is the breakdown of an engine during flight or the use of unpowered stand …
Terminal adaptive guidance for autonomous hypersonic strike weapons via reinforcement learning
An adaptive guidance system suitable for the terminal phase trajectory of a hypersonic strike
weapon is optimized using reinforcement meta learning. The guidance system maps …
weapon is optimized using reinforcement meta learning. The guidance system maps …
Time-coordination entry guidance using a range-determined strategy
H Wang, J Guo, X Wang, X Li, S Tang - Aerospace Science and …, 2022 - Elsevier
A time-coordination entry guidance method based on a range-determined strategy is
developed for hypersonic glide vehicles. This method is composed of two components: a …
developed for hypersonic glide vehicles. This method is composed of two components: a …
Line of sight curvature for missile guidance using reinforcement meta-learning
View Video Presentation: https://doi. org/10.2514/6.2023-1627. vid We use reinforcement
meta learning to optimize a line of sight curvature policy that increases the effectiveness of a …
meta learning to optimize a line of sight curvature policy that increases the effectiveness of a …
A Comparison of Partially and Fully Integrated Guidance and Flight Control Optimized with Reinforcement Meta-Learning
View Video Presentation: https://doi. org/10.2514/6.2023-1628. vid We use reinforcement
meta-learning to optimize and evaluate two integrated guidance and flight control systems …
meta-learning to optimize and evaluate two integrated guidance and flight control systems …