TY - GEN
T1 - RSD
T2 - 2023 China Automation Congress, CAC 2023
AU - Gao, Xiang
AU - Guo, Weixia
AU - Huang, Guanjie
AU - Zheng, Yuchen
AU - Xie, Chengyun
AU - Dong, Liangyu
AU - Cui, Lingguo
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - As global temperatures increase, forest fires have increased in frequency and size. The multi-robot system can monitor the fire spread trend in real-time and provide effective information for the global decision-making center. Furthermore, attackers may prevent some robots from making optimal decisions. Therefore, this paper studies the multi-robot cooperative forest fire monitoring problem under cyber attacks, where each robot has the ability to make autonomous decisions. First, the forest fire monitoring problem is considered as a maximum area coverage problem, and the single-step actions of each robot are selected based on the principle of maximizing the submodular function. Based on this, this paper proposes a robust decision-making algorithm that can minimize the attacker's influence on the decision, even in the worst case. Finally, the simulation results verify that the proposed algorithm can achieve maximum forest fire monitoring.
AB - As global temperatures increase, forest fires have increased in frequency and size. The multi-robot system can monitor the fire spread trend in real-time and provide effective information for the global decision-making center. Furthermore, attackers may prevent some robots from making optimal decisions. Therefore, this paper studies the multi-robot cooperative forest fire monitoring problem under cyber attacks, where each robot has the ability to make autonomous decisions. First, the forest fire monitoring problem is considered as a maximum area coverage problem, and the single-step actions of each robot are selected based on the principle of maximizing the submodular function. Based on this, this paper proposes a robust decision-making algorithm that can minimize the attacker's influence on the decision, even in the worst case. Finally, the simulation results verify that the proposed algorithm can achieve maximum forest fire monitoring.
KW - Natural disaster monitoring
KW - cyber attacks
KW - multi-robot systems
KW - safety decision-making
KW - submodar maximization
UR - http://www.scopus.com/inward/record.url?scp=85189351691&partnerID=8YFLogxK
U2 - 10.1109/CAC59555.2023.10451484
DO - 10.1109/CAC59555.2023.10451484
M3 - Conference contribution
AN - SCOPUS:85189351691
T3 - Proceedings - 2023 China Automation Congress, CAC 2023
SP - 2652
EP - 2657
BT - Proceedings - 2023 China Automation Congress, CAC 2023
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 17 November 2023 through 19 November 2023
ER -