With the development of power grid intelligence, substations as a critical component of the power grid its safety and reliability directly impact the overall security and reliability of the grid’s power supply. In order to maintain substation power supply reliability, and improve inspection robot inspection efficiency. This study presents a Glasius Bio-Inspired Neural Network (GBNN) algorithm for autonomous path planning in collaborative multi-robot systems designed to perform multi-target inspections in smart substations. The approach begins with constructing a standard GBNN model that incorporates the substation’s environmental characteristics. Subsequently, neuron activation values are updated using the GBNN algorithm. Simulations demonstrate the algorithm’s effectiveness in enabling efficient path planning for multi-robot, multi-task inspections in dynamic and uncertain environments.
GasparJCruzTLamC, et al.Smart substation communications and cybersecurity: a comprehensive survey. IEEE Commun Surv Tutorials2023; 25: 2456–2493.
2.
ZhangGDuZZhangY, et al.Real-time performance evaluation and optimization of electrical substation equipment inspection algorithm based on distributed computing. Int J Low-Carbon Technol2024; 19: 1878–1887.
3.
JiangQLiuYYanY, et al.Active pose relocalization for intelligent substation inspection robot. IEEE Trans Ind Electron2023; 70: 4972–4982.
4.
GasparJCruzTLamC-T, et al.Smart substation communications and cybersecurity: a comprehensive survey. IEEE Commun Surv Tutorials2023; 25: 2456–2493.
5.
HuangJWangJTanY, et al.An automatic analog instrument reading system using computer vision and inspection robot. IEEE Trans Instrum Meas2020; 69: 6322–6335.
6.
LiZTianYYangG, et al.Model-based trajectory planning of a hybrid robot for powerline inspection. IEEE Rob Autom Lett2024; 9: 3443–3450.
7.
ZhongXTianJHuH, et al.Hybrid path planning based on safe A* algorithm and adaptive window approach for mobile robot in large-scale dynamic environment. J Intell Rob Syst2020; 99: 65–77.
8.
LiuLSLinJFYaoJX, et al.Path planning for smart car based on Dijkstra algorithm and dynamic window approach. Wireless Commun Mobile Comput2021; 15: 1–2.
9.
LinZYueMChenG, et al.Path planning of mobile robot with PSO-based APF and fuzzy-based DWA subject to moving obstacles. Trans Inst Meas Control2022; 44: 121–132.
10.
CaoXRenLSunC. Research on obstacle detection and avoidance of autonomous underwater vehicle based on forward-looking sonar. IEEE Trans Neural Netw Learn Syst2022; 34: 9198–9208.
11.
GanYZhangBKeC, et al.Research on robot motion planning based on RRT algorithm with nonholonomic constraint. Neural Process Lett2021; 53: 3011–3029.
12.
HanSWangLWangY, et al.An efficient motion planning based on grid map: predicted trajectory approach with global path guiding. Ocean Eng2021; 238: 109696.
13.
ZouQCongMLiuD, et al.A neurobiologically inspired mapping and navigating framework for mobile robots. Neurocomputing2021; 2460: 181–194.
14.
LinZWuKShenR, et al.An efficient and accurate A-star algorithm for autonomous vehicle path planning. IEEE Trans Veh Technol2024; 73: 9003–9008.
15.
SzczepanskiR. Safe artificial potential field-novel local path planning algorithm maintaining safe distance from obstacles. IEEE Rob Autom Lett2023; 8: 4823–4830.
16.
YaoPQiuLQiJ, et al.AUV path planning for coverage search of static target in ocean environment. Ocean Eng2021; 241: 110050.
17.
SunBZhuDTianC, et al.Complete coverage autonomous underwater vehicles path planning based on glasius bio-inspired neural network algorithm for discrete and centralized programming. IEEE Trans Cognit Dev Syst2019; 11: 73–84.
18.
ChenMZhuD. Optimal time-consuming path planning for autonomous underwater vehicles based on a dynamic neural network model in ocean current environments. IEEE Trans Veh Technol2020; 69: 14401–14412.
19.
YiLWanALeA, et al.Complete coverage path planning for reconfigurable omni-directional mobile robots with varying width using GBNN (n). Expert Syst Appl2023; 228: 120349.
20.
RodrigoDVSierra-GarcíaJESantosM. Glasius bio-inspired neural networks based UV-C disinfection path planning improved by preventive deadlock processing algorithm. Adv Eng Software2023; 175: 103330.
21.
YaoPZhaoZ. Improved Glasius bio-inspired neural network for target search by multi-agents. Inf Sci (Ny)2021; 568: 40–53.
22.
ZhangWFengXSunB. Glasius bio-inspired neural network algorithm based substation inspection robot dynamic path planning. Int J Rob Autom2024; 39: 211–219.
23.
WanAYiLHayatA, et al.Complete area-coverage path planner for surface cleaning in hospital settings using mobile dual-arm robot and GBNN with heuristics. Complex Intell Syst2024; 10: 6767–6785.
