TY - JOUR
T1 - Collaborative Defense with Multiple USVs and UAVs Based on Swarm Intelligence
AU - Wu, Xing
AU - Liu, Yuan
AU - Xie, Shaorong
AU - Guo, Yi-Ke
N1 - Publisher Copyright:
© 2019, Shanghai Jiao Tong University and Springer-Verlag GmbH Germany, part of Springer Nature.
PY - 2020/2/1
Y1 - 2020/2/1
N2 - Modern defense systems are developing towards systematization, intellectualization and automation, which include the collaborative defense system on the sea between multiple unmanned surface vehicles (USVs) and unmanned aerial vehicles (UAVs). UAVs can fly in high altitude and collect marine environment information on patrolling. Furthermore, UAVs can plan defense paths for USVs to intercept intruders with full-assignment or reassignment strategies aiming at maximum overall benefits. Thus, we propose dynamic overlay reconnaissance algorithm based on genetic idea (GI-DORA) to solve the problem of multi-UAV multi-station reconnaissance. Moreover, we develop continuous particle swarm optimization based on obstacle dimension (OD-CPSO) to optimize defense path of USVs to intercept intruders. In addition, under the designed defense constraints, we propose dispersed particle swarm optimization based on mutation and crossover (MC-DPSO) and real-time batch assignment algorithm (RTBA) in emergency for formulating combat defense mission assignment strategy in different scenarios. Finally, we illustrate the feasibility and effectiveness of the proposed methods.
AB - Modern defense systems are developing towards systematization, intellectualization and automation, which include the collaborative defense system on the sea between multiple unmanned surface vehicles (USVs) and unmanned aerial vehicles (UAVs). UAVs can fly in high altitude and collect marine environment information on patrolling. Furthermore, UAVs can plan defense paths for USVs to intercept intruders with full-assignment or reassignment strategies aiming at maximum overall benefits. Thus, we propose dynamic overlay reconnaissance algorithm based on genetic idea (GI-DORA) to solve the problem of multi-UAV multi-station reconnaissance. Moreover, we develop continuous particle swarm optimization based on obstacle dimension (OD-CPSO) to optimize defense path of USVs to intercept intruders. In addition, under the designed defense constraints, we propose dispersed particle swarm optimization based on mutation and crossover (MC-DPSO) and real-time batch assignment algorithm (RTBA) in emergency for formulating combat defense mission assignment strategy in different scenarios. Finally, we illustrate the feasibility and effectiveness of the proposed methods.
KW - A
KW - collaborative defense
KW - mission assignment
KW - path planning
KW - TP 399
KW - unmanned aerial vehicles (UAVs)
KW - unmanned surface vehicles (USVs)
UR - http://www.scopus.com/inward/record.url?scp=85076742342&partnerID=8YFLogxK
U2 - 10.1007/s12204-019-2142-y
DO - 10.1007/s12204-019-2142-y
M3 - Journal article
AN - SCOPUS:85076742342
SN - 1007-1172
VL - 25
SP - 51
EP - 56
JO - Journal of Shanghai Jiaotong University (Science)
JF - Journal of Shanghai Jiaotong University (Science)
IS - 1
ER -