Compared with the model-based method which could perform poorly under model uncertainties or stochastic environments, the learning-based method uses no information about robot model, thus is not subject to the model uncertainties.
This paper aims to provide a brief overview of our recent development of learning-based formation control, and compare it with a model-based method.
Jan 2, 2020 · This paper aims to provide a brief overview of our recent development of learning-based formation control, and compare it with a model-based ...
Dec 6, 2019 · The results show that the proposed ERGM-based choice modelling achieves higher accuracy in predicting both individual choice behaviours and ...
Multi-robot formation control: a comparison between model-based and learning-based methods · Full Article · Figures & data · References · Citations · Metrics ...
This paper aims to provide a brief overview of our recent development of learning-based formation control, and compare it with a model-based method for a case ...
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Multi-robot formation control: A comparison between model-based and learning-based methods. Article. Dec 2019. Chao Jiang · Zhuo Chen · Yi Guo. Formation ...
Jan 31, 2023 · This paper investigates the problem of multi-robot formation control strategies in environments with obstacles based on deep reinforcement learning methods.
Decentralized formation control has been extensively studied using model-based methods, which rely on model accuracy and communication reliability.
[PDF] Learning Decentralized Control Policies for Multi-Robot Formation
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Compared with existing model-based formation control methods with relative formation errors of 1% − 10% in general ([3]), the performance of our learning ...