Zobrazeno 1 - 10
of 165
pro vyhledávání: '"Gaudet Brian"'
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 maximize the total value of destroyed targets in each episode. Each rand
Externí odkaz:
http://arxiv.org/abs/2310.18509
Autor:
Gaudet, Brian, Furfaro, Roberto
We use reinforcement meta learning to optimize a line of sight curvature policy that increases the effectiveness of a guidance system against maneuvering targets. The policy is implemented as a recurrent neural network that maps navigation system out
Externí odkaz:
http://arxiv.org/abs/2205.00085
Autor:
Tai, Sheng-Lun, Gaudet, Brian, Feng, Sha, Krishnamurthy, Raghavendra, Berg, Larry K., Fast, Jerome D.
Publikováno v:
In Renewable Energy 1 February 2025 239
Autor:
Gaudet, Brian, Furfaro, Roberto
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. The seeker tracks the designated landing site by adjusting seeker el
Externí odkaz:
http://arxiv.org/abs/2112.08540
Autor:
Gaudet, Brian, Furfaro, Roberto
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 observations directly to commanded bank angle, angle of attack, and sideslip
Externí odkaz:
http://arxiv.org/abs/2110.00634
Integrated and Adaptive Guidance and Control for Endoatmospheric Missiles via Reinforcement Learning
Autor:
Gaudet, Brian, Furfaro, Roberto
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 policy that maps navigation system outputs directly to commanded rate
Externí odkaz:
http://arxiv.org/abs/2109.03880
We use Reinforcement Meta Learning to optimize an adaptive guidance system suitable for the approach phase of a gliding hypersonic vehicle. Adaptability is achieved by optimizing over a range of off-nominal flight conditions including perturbation of
Externí odkaz:
http://arxiv.org/abs/2107.14764
Autor:
Shrivastava, Manish, Fan, Jiwen, Zhang, Yuwei, Rasool, Quazi Z., Zhao, Bin, Shen, Jiewen, Pierce, Jeffrey R., Jathar, Shantanu H., Akherati, Ali, Zhang, Jie, Zaveri, Rahul A., Gaudet, Brian, Liu, Ying, Andreae, Meinrat O., Pöhlker, Mira L., Donahue, Neil M., Wang, Yuan, Seinfeld, John H.
Publikováno v:
In One Earth 21 June 2024 7(6):1029-1043
Autor:
Gaudet, Brian
In this work we present a method to adaptively compensate for scale factor errors in both rotational velocity and seeker angle measurements. The adaptation scheme estimates the scale factor errors using a predictive coding model implemented as a deep
Externí odkaz:
http://arxiv.org/abs/2009.00975
We use Reinforcement Meta-Learning to optimize an adaptive integrated guidance, navigation, and control system suitable for exoatmospheric interception of a maneuvering target. The system maps observations consisting of strapdown seeker angles and ra
Externí odkaz:
http://arxiv.org/abs/2004.09978