Page 124 - Read Online
P. 124
Page 72 Guan et al. Intell Robot 2024;4(1):61-73 I http://dx.doi.org/10.20517/ir.2024.04
local optimum solutions, so that it can better serve the optimization of controller parameters. This presents
an exciting direction for future work. Subsequent research is needed to validate these prospects, but the inte-
gration of these two algorithms could potentially provide a powerful tool for tackling complex optimization
problems.
DECLARATIONS
Authors’ contributions
Significantly contributed to the conceptualization of the study and the methodology proposed and performed
the validation, analysis, investigation, resource acquisition, and writing: Guan J
Performed article review and editing, project supervision and management: Cheng H
Availability of data and materials
Not applicable.
Financial support and sponsorship
None.
Conflicts of interest
Both authors declared that there are no conflicts of interest
Ethical approval and consent to participate
Not applicable.
Consent for publication
Not applicable.
Copyright
© The Author(s) 2024.
REFERENCES
1. Tong B, Wei C, Shi Y. Fractional order darwinian pigeon-inspired optimization for multi-UAV swarm controller. Guid Navig Control
2022;2:2250010. DOI
2. Consolini L, Morbidi F, Prattichizzo D, Tosques M. Leader-follower formation control of nonholonomic mobile robots with input con-
straints. Automatica 2008;44;1343-49. DOI
3. Duan H, Qiao P. Pigeon-inspired optimization: a new swarm intelligence optimizer for air robot path planning. Int J Intell Comput
Cybernet 2014;7;24-37. DOI
4. Zhang B, Duan H. Three-dimensional path planning for uninhabited combat aerial vehicle based on predator-prey pigeon-inspired opti-
mization in dynamic environment. IEEE/ACM Trans Comput Biol Bioinformat 2017;14:97-107. DOI
5. Duan H, Wang X. Echo state networks with orthogonal pigeon-inspired optimization for image restoration. IEEE Trans Neural Netw
Learn Syst 2016;27;2413-25. DOI
6. Duan H, Qiu H. Advancements in pigeon-inspired optimization and its variants. Sci Chin Informat Sci 2019;62:70201. DOI
7. Hu Q, Zhang MS. A collaborative optimization for floorplanning and pin assignment of 3D ICs based on GA-SA algorithm. In: 2020
IEEE International Symposium on Electromagnetic Compatibility & Signal/Power Integrity (EMCSI); 2020 Jul 28 - Aug 28; Reno, NV,
USA. IEEE; 2020. pp.434-8. DOI
8. Yang C, Chen R, Wang W, Li Y, Shen X, Xiang C. Cyber-physical optimization-based fuzzy control strategy for plug-in hybrid electric
buses using iterative modified particle swarm optimization. IEEE Trans Intell Veh 2023;8:3285-98. DOI
9. Rezaee H, Abdollahi F, Menhaj MB. Model-free fuzzy leader-follower formation control of fixed wing UAVs. In: 2013 13th Iranian
Conference on Fuzzy Systems (IFSC); 2013 Aug 27-29; Qazvin, Iran. IEEE; 2013. pp.1-5. DOI
10. Tong B, Chen L, Duan H. A path planning method for UAVs based on multi-objective pigeon-inspired optimisation and differential
evolution. Int J Bio-Inspired Comput 2021;17;105-12. DOI
11. Zong L, Xie F, Qin S. Intelligent optimizing control of formation flight for UAVs based on MAS. Acta Aeronaut Astronaut Sin
2008;29:1326-33. Available from: https://hkxb.buaa.edu.cn/EN/abstract/abstract9316.shtml. [Last accessed on 4 March 2024]