Reinforcement-Learning-Based Task Planning for Self-Reconfiguration of Cellular Satellites

Zhang, Yizhai; Wang, Wenhui; Zhang, Piaoqi; Huang, Panfeng

doi:10.1109/maes.2021.3089252

Cited by 4 publications

(1 citation statement)

References 23 publications

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“…1 Cellular satellite is a module of satellite, which has the characteristics of independent function, standardized interface, and reconfiguration. Considering the advantages of low cost, fast response, and on-orbit assembly, 2 many researches have focused on the cellular satellites, such as Phoenix program, 3 and iBOSS project. 4 When the attitude control system fails, the entire spacecraft will not work and the important components on spacecraft will be wasted.…”

Section: Introductionmentioning

confidence: 99%

Predefined-time attitude takeover control of spacecraft with quantized states

Shi

2023

Proceedings of the Institution of Mechanical Engineers, Part G:

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This article addresses the problem of predefined-time attitude takeover control (PTATC) of spacecraft by using cellular satellites with limited inter-satellite communication capacity. To reduce the communication burden in the wireless networks, a dynamic uniform quantizer is employed to quantize the attitude signals and angular velocity signals measured by the sensor cellular satellites (SCSs). Besides, a static uniform quantizer is used to quantize the control torque signal generated by the controller cellular satellite (CCS). A predefined-time quantized attitude control law is designed, which can compensate for the quantization error. The proposed PTATC scheme can reduce the communication burden among the cellular satellites and achieve the desired angular velocity and attitude of the combined spacecraft within the predefined-time on the premise of ensuring the system performance. Under the proposed control law, all the signals in the closed-loop system can converge into a bounded region within a predefined-time. Finally, numerical simulations are presented to illustrate the effectiveness of the proposed scheme.

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Section: Introductionmentioning

confidence: 99%

Predefined-time attitude takeover control of spacecraft with quantized states

Shi

2023

Proceedings of the Institution of Mechanical Engineers, Part G:

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Beyond games: a systematic review of neural Monte Carlo tree search applications

Kemmerling,

Lütticke,

Schmitt

2023

Appl Intell

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The advent of AlphaGo and its successors marked the beginning of a new paradigm in playing games using artificial intelligence. This was achieved by combining Monte Carlo tree search, a planning procedure, and deep learning. While the impact on the domain of games has been undeniable, it is less clear how useful similar approaches are in applications beyond games and how they need to be adapted from the original methodology. We perform a systematic literature review of peer-reviewed articles detailing the application of neural Monte Carlo tree search methods in domains other than games. Our goal is to systematically assess how such methods are structured in practice and if their success can be extended to other domains. We find applications in a variety of domains, many distinct ways of guiding the tree search using learned policy and value functions, and various training methods. Our review maps the current landscape of algorithms in the family of neural monte carlo tree search as they are applied to practical problems, which is a first step towards a more principled way of designing such algorithms for specific problems and their requirements.

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Multi-Modal Multi-Agent Optimization for LIMMS, A Modular Robotics Approach to Delivery Automation

Fernandez

Yeting

et al. 2022

2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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Reinforcement-Learning-Based Task Planning for Self-Reconfiguration of Cellular Satellites

Cited by 4 publications

References 23 publications

Predefined-time attitude takeover control of spacecraft with quantized states

Predefined-time attitude takeover control of spacecraft with quantized states

Beyond games: a systematic review of neural Monte Carlo tree search applications

Multi-Modal Multi-Agent Optimization for LIMMS, A Modular Robotics Approach to Delivery Automation

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