System design and resource analysis for persistent robotic presence with multiple refueling stations
被引:0
作者:
Park, Hyorin
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机构:
Korea Adv Inst Sci & Technol, Dept Ind & Syst Engn, 373-1 Guseong Dong, Daejeon 305701, South KoreaKorea Adv Inst Sci & Technol, Dept Ind & Syst Engn, 373-1 Guseong Dong, Daejeon 305701, South Korea
Park, Hyorin
[1
]
Morrison, James R.
论文数: 0引用数: 0
h-index: 0
机构:
Korea Adv Inst Sci & Technol, Dept Ind & Syst Engn, 373-1 Guseong Dong, Daejeon 305701, South KoreaKorea Adv Inst Sci & Technol, Dept Ind & Syst Engn, 373-1 Guseong Dong, Daejeon 305701, South Korea
Morrison, James R.
[1
]
机构:
[1] Korea Adv Inst Sci & Technol, Dept Ind & Syst Engn, 373-1 Guseong Dong, Daejeon 305701, South Korea
来源:
2019 INTERNATIONAL CONFERENCE ON UNMANNED AIRCRAFT SYSTEMS (ICUAS' 19)
|
2019年
关键词:
UAVS;
D O I:
10.1109/icuas.2019.8797808
中图分类号:
TM [电工技术];
TN [电子技术、通信技术];
学科分类号:
0808 ;
0809 ;
摘要:
Despite the capabilities of unmanned aerial vehicles (UAVs), it is not possible to conduct long-term missions with a just few UAVs due to fuel restrictions. This requires a system that includes multiple UAVs and automated recharging stations for an automatic and persistent service. In order to construct a persistent presence system such as local surveillance and monitoring, it is important to determine the design of the mission and the number of resources required. In this paper, a system consisting of multiple target areas and multiple stations is considered. There arc two types of stations: refueling and main stations for maintenance. UAVs can travel further using the refueling stations. A decision-free Petri net model for persistency is developed for cyclic paths including multiple immobile targets and stations. From the Petri net model, we derive a closed-form function for the minimum number of resources in the persistent system. A mathematical model that has the objective function derived from the Petri net is developed. To resolve the computational issue, a genetic algorithm (GA) is used to solve the problem. As the result, the minimum number of resources required and the mission path are derived.