Decentralized Cooperative Search in UAV's Using Opportunistic Learning

In this paper, we present a complex cooperative search technique for finding the Random Walking microorganism cells on one of [Formula: see text]-intersect real lines at the origin. We have 2[Formula: see text] unit speed searchers starting together from the origin. Furthermore, proving the existence of a finite search plan, we are discussing the existence of optimality for this search plan which minimizes the expected value of the first meeting time between one of the searchers and the microorganism cells.

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Multiple UAVs Cooperative Search Based on Potential Game Theory

2019 IEEE International Conference on Consumer Electronics - Taiwan (ICCE-TW) ◽

10.1109/icce-tw46550.2019.8991876 ◽

2019 ◽

Author(s):

Jianjun Ni ◽

Zhengpei Mo ◽

Weidong Cao ◽

Chengming Luo

Keyword(s):

Game Theory ◽

Potential Game ◽

Cooperative Search ◽

Multiple Uavs

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Cooperative Search Using Agents for Cardinality Constrained Portfolio Selection Problem

IEEE Transactions on Systems Man and Cybernetics Part C (Applications and Reviews) ◽

10.1109/tsmcc.2012.2197388 ◽

2012 ◽

Vol 42 (6) ◽

pp. 1510-1518 ◽

Cited By ~ 9

Author(s):

Ritesh Kumar ◽

Subir Bhattacharya

Keyword(s):

Portfolio Selection ◽

Selection Problem ◽

Cooperative Search ◽

Portfolio Selection Problem

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Multi-AUV Underwater Cooperative Search Algorithm based on Biological Inspired Neurodynamics Model and Velocity Synthesis

Journal of Navigation ◽

10.1017/s0373463315000351 ◽

2015 ◽

Vol 68 (6) ◽

pp. 1075-1087 ◽

Cited By ~ 7

Author(s):

Xiang Cao ◽

Daqi Zhu

Keyword(s):

Autonomous Underwater Vehicle ◽

Search Algorithm ◽

Integrated Approach ◽

Underwater Vehicle ◽

Ocean Currents ◽

Ocean Current ◽

Cooperative Search ◽

Search Path ◽

Negative Effect ◽

Underwater Target

Ocean currents impose a negative effect on Autonomous Underwater Vehicle (AUV) underwater target searches, which lengthens the search paths and consumes more energy and team effort. To solve this problem, an integrated algorithm is proposed to realise multi-AUV cooperative search in dynamic underwater environments with ocean currents. The proposed integrated algorithm combines the Biological Inspired Neurodynamics Model (BINM) and Velocity Synthesis (VS) method. Firstly, the BINM guides a team of AUVs to achieve target search in underwater environments; BINM search requires no specimen learning information and is thus easier to apply to practice, but the search path is longer because of the influence of ocean current. Next the VS algorithm offsets the effect of ocean current, and it is applied to optimise the search path for each AUV. Lastly, to demonstrate the effectiveness of the proposed integrated approach, simulation results are given in this paper. It is proved that this integrated algorithm can plan shorter search paths and thus the energy consumption is lower compared with BINM.

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