no code implementations • 27 Oct 2023 • Brian Gaudet, Kris Drozd, Roberto Furfaro
We use deep reinforcement learning (RL) to optimize a weapons to target assignment (WTA) policy for multi-vehicle hypersonic strike against multiple targets.
no code implementations • 16 Dec 2021 • Brian Gaudet, Roberto Furfaro
We develop an integrated guidance and control system that in conjunction with a stabilized seeker and landing site detection software can achieve precise and safe planetary landing.
no code implementations • 1 Oct 2021 • Brian Gaudet, Roberto Furfaro
An adaptive guidance system suitable for the terminal phase trajectory of a hypersonic strike weapon is optimized using reinforcement meta learning.
no code implementations • 8 Sep 2021 • Brian Gaudet, Roberto Furfaro
We apply a reinforcement meta-learning framework to optimize an integrated and adaptive guidance and flight control system for an air-to-air missile.
no code implementations • 30 Jul 2021 • Brian Gaudet, Kris Drozd, Ryan Meltzer, Roberto Furfaro
We use Reinforcement Meta Learning to optimize an adaptive guidance system suitable for the approach phase of a gliding hypersonic vehicle.
1 code implementation • 18 Apr 2020 • Brian Gaudet, Roberto Furfaro, Richard Linares, Andrea Scorsoglio
We use Reinforcement Meta-Learning to optimize an adaptive integrated guidance, navigation, and control system suitable for exoatmospheric interception of a maneuvering target.
no code implementations • 16 Nov 2019 • Brian Gaudet, Richard Linares, Roberto Furfaro
This allows the deployed policy to generalize well to novel asteroid characteristics, which we demonstrate in our experiments.
no code implementations • 13 Jul 2019 • Brian Gaudet, Richard Linares, Roberto Furfaro
Finally, we suggest a concept of operations for asteroid close proximity maneuvers that is compatible with the guidance system.
no code implementations • 5 Jun 2019 • Brian Gaudet, Roberto Furfaro, Richard Linares
We present a novel guidance law that uses observations consisting solely of seeker line of sight angle measurements and their rate of change.
Systems and Control
no code implementations • 18 Apr 2019 • Brian Gaudet, Richard Linares, Roberto Furfaro
We also demonstrate the ability of a RL meta-learning optimized policy to implement a guidance law using observations consisting of only Doppler radar altimeter readings in a Mars landing environment, and LIDAR altimeter readings in an asteroid landing environment, thus integrating guidance and navigation.
Systems and Control
no code implementations • 12 Jan 2019 • Brian Gaudet, Richard Linares, Roberto Furfaro
Instead, we learn a mapping from the first observation in an episode to the hidden state, allowing the trained model to immediately produce accurate predictions.
no code implementations • 20 Oct 2018 • Brian Gaudet, Richard Linares, Roberto Furfaro
The latter requires both a navigation system capable of estimating the lander's state in real-time and a guidance and control system that can map the estimated lander state to a commanded thrust for each lander engine.
Systems and Control