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Fast Transfer Navigation for Autonomous Robots.
- Source :
- Journal of Robotics; 12/2/2021, p1-7, 7p
- Publication Year :
- 2021
-
Abstract
- Navigation technology enables indoor robots to arrive at their destinations safely. Generally, the varieties of the interior environment contribute to the difficulty of robotic navigation and hurt their performance. This paper proposes a transfer navigation algorithm and improves its generalization by leveraging deep reinforcement learning and a self-attention module. To simulate the unfurnished indoor environment, we build the virtual indoor navigation (VIN) environment to compare our model and its competitors. In the VIN environment, our method outperforms other algorithms by adapting to an unseen indoor environment. The code of the proposed model and the virtual indoor navigation environment will be released. [ABSTRACT FROM AUTHOR]
- Subjects :
- AUTONOMOUS robots
DEEP learning
REINFORCEMENT learning
ROBOTICS
ALGORITHMS
Subjects
Details
- Language :
- English
- ISSN :
- 16879600
- Database :
- Complementary Index
- Journal :
- Journal of Robotics
- Publication Type :
- Academic Journal
- Accession number :
- 153924933
- Full Text :
- https://doi.org/10.1155/2021/3028319