一种用于机器人电池电量预测的 Sarsa 强化学习混合集成方法
Author:
Publisher
Springer Science and Business Media LLC
Subject
Metals and Alloys,General Engineering
Link
https://link.springer.com/content/pdf/10.1007/s11771-023-5451-0.pdf
Reference60 articles.
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3. HERCIK R, BYRTUS R, JAROS R, et al. Implementation of autonomous mobile robot in SmartFactory [J]. Applied Sciences, 2022, 12(17): 8912. DOI: https://doi.org/10.3390/app12178912.
4. DAIM T U, YOON B S, LINDENBERG J, et al. Strategic roadmapping of robotics technologies for the power industry: A multicriteria technology assessment [J]. Technological Forecasting and Social Change, 2018, 131: 49–66. DOI: https://doi.org/10.1016/j.techfore.2017.06.006.
5. ZHANG Han-ye, LIN Wei-ming, CHEN Ai-xia. Path planning for the mobile robot: A review [J]. Symmetry, 2018, 10(10): 450. DOI: https://doi.org/10.3390/sym10100450.
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