2020
DOI: 10.48550/arxiv.2003.01641
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Efficient Exploration in Constrained Environments with Goal-Oriented Reference Path

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Cited by 4 publications
(3 citation statements)
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“…In other words, model-based methods lack scalability and customizability. The data collected by the model-based methods can be used to train learningbased algorithms, particularly deep learning [15]- [21]. These algorithms can infer a path for a new environment in a short time if it has trained sufficiently in advance.…”
Section: Related Workmentioning
confidence: 99%
“…In other words, model-based methods lack scalability and customizability. The data collected by the model-based methods can be used to train learningbased algorithms, particularly deep learning [15]- [21]. These algorithms can infer a path for a new environment in a short time if it has trained sufficiently in advance.…”
Section: Related Workmentioning
confidence: 99%
“…In other words, model-based methods lack scalability and customizability. The data collected by the model-based methods can be used to train learning-based algorithms, particularly deep learning [12,13,14,15,16,17,18]. These algorithms can infer a path for a new environment in a short time if it has trained sufficiently in advance.…”
Section: Related Workmentioning
confidence: 99%
“…The study concluded that a mapless motion planner based on the DDPG algorithm can be successfully trained and used to complete the task of navigating to a target. Zhu et al [5], Chen et al [21], Ota et al [22], de Jesus et al [23] and others have already successfully applied Deep-RL approaches to perform mapless navigation-related tasks for terrestrial mobile robots.…”
Section: Related Workmentioning
confidence: 99%