Multi-USV System Cooperative Underwater Target Search Based on Reinforcement Learning and Probability Map
المؤلفون المشاركون
Liu, Yuan
Peng, Yan
Wang, Min
Xie, Jiajia
Zhou, Rui
المصدر
Mathematical Problems in Engineering
العدد
المجلد 2020، العدد 2020 (31 ديسمبر/كانون الأول 2020)، ص ص. 1-12، 12ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2020-05-14
دولة النشر
مصر
عدد الصفحات
12
التخصصات الرئيسية
الملخص EN
Unmanned surface vehicle (USV) is a robotic system with autonomous planning, driving, and navigation capabilities.
With the continuous development of applications, the missions faced by USV are becoming more and more complex, so it is difficult for a single USV to meet the mission requirements.
Compared with a single USV, a multi-USV system has some outstanding advantages such as fewer perceptual constraints, larger operation ranges, and stronger operation capability.
In the search mission about multiple stationary underwater targets by a multi-USV system in the environment with obstacles, we propose a novel cooperative search algorithm (CSBDRL) based on reinforcement learning (RL) method and probability map method.
CSBDRL is composed of the environmental sense module and policy module, which are organized by the “divide and conquer” policy-based architecture.
The environmental sense module focuses on providing environmental sense values by using the probability map method.
The policy module focuses on learning the optimal policy by using RL method.
In CSBDRL, the mission environment is modeled and the corresponding reward function is designed to effectively explore the environment and learning policies.
We test CSBDRL in the simulation environment and compare it with other methods.
The results prove that compared with other methods, CSBDRL makes the multi-USV system have a higher search efficiency, which can ensure targets are found more quickly and accurately while ensuring the USV avoids obstacles in time during the mission.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Liu, Yuan& Peng, Yan& Wang, Min& Xie, Jiajia& Zhou, Rui. 2020. Multi-USV System Cooperative Underwater Target Search Based on Reinforcement Learning and Probability Map. Mathematical Problems in Engineering،Vol. 2020, no. 2020, pp.1-12.
https://search.emarefa.net/detail/BIM-1200708
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Liu, Yuan…[et al.]. Multi-USV System Cooperative Underwater Target Search Based on Reinforcement Learning and Probability Map. Mathematical Problems in Engineering No. 2020 (2020), pp.1-12.
https://search.emarefa.net/detail/BIM-1200708
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Liu, Yuan& Peng, Yan& Wang, Min& Xie, Jiajia& Zhou, Rui. Multi-USV System Cooperative Underwater Target Search Based on Reinforcement Learning and Probability Map. Mathematical Problems in Engineering. 2020. Vol. 2020, no. 2020, pp.1-12.
https://search.emarefa.net/detail/BIM-1200708
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1200708
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر