Robot navigation path planning in power plant based on improved wolf pack algorithm

Wang, Zhan; Yu, Rongdong; Yang, Tao; Xu, Jie; Meng, Yuwei

doi:10.1145/3482632.3487523

Cited by 4 publications

(2 citation statements)

References 3 publications

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“…For substation inspection robots, a novel cross-entropy optimization-based heuristic route planning method was proposed (Wang et al, 2021). The shortest route among the simplified task points is computed using the cross-entropy optimization technique.…”

Section: Literature Reviewmentioning

confidence: 99%

Implementation of PID controller and enhanced red deer algorithm in optimal path planning of substation inspection robots

Tang,

Xue,

et al. 2024

Journal of Field Robotics

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In contemporary power transmission systems, substation monitoring stands as a vital but challenging task. While robotics offers promise in this regard, its potential is still nascent, struggling to replicate human intelligence. This article's core aim was to optimize robot path planning (RPP). Employing the enhanced red deer algorithm (ERDA), we sought to bolster RPP for more efficient substation inspections. The key methods used seem to be modeling, experimentation, comparative analysis, and some elements of data benchmarking to systematically evaluate and validate their proposed technique and models both in simulation and the real world. Research aims to enhance substation inspection effectiveness and bolster the safety of power usage in society. Proposed hybrid approach, combining proportional–integral–derivative (PID) with ERDA (PID–ERDA), underpins an Intelligent Intelligent RPP framework tailored to substation inspections. Examining the PID–ERDA model's performance, it significantly improved path length by 18%–29% and reduced response times by 14%–26% compared with PID or ERDA alone. PID–ERDA consistently achieved optimal solutions in 40–60 trials out of 85, while PID and ERDA managed 20–40 trials with inconsistent optimization. Additionally, it reduced average response times to 17–20 s from 21 to 27 s observed when using PID and ERDA separately. PID–ERDA also demonstrated superior path accuracy, surpassing methods like improved adaptive control algorithm‐feedforward neural network, enhanced unified algorithm‐susceptible‐infected‐removed, and bounded behavior‐particle swarm optimization by 7%–13%. The study affirms that the PID–ERDA model significantly enhances path planning for substation inspections, representing a milestone in RPP for power station inspections within modern power transmission systems. The primary contribution of this research is the significant improvement it brings to RPP for power station inspections, especially in substation monitoring within modern power transmission systems.

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Section: Literature Reviewmentioning

confidence: 99%

Implementation of PID controller and enhanced red deer algorithm in optimal path planning of substation inspection robots

Tang,

Xue,

et al. 2024

Journal of Field Robotics

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“…However, the implementation of reproductive behavior may get the algorithm into the local optimal solution or premature convergence. Therefore, we need to consider the crossover rate and variation rate [5].…”

Section: Introductionmentioning

confidence: 99%

UAV Path Planning Method Based on Improved Wolf Pack Algorithm

2023

jeis

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At present, there are more and more situations using drones to perform missions, and the working environment of drones is becoming more and more complex. Path planning has become the basic premise for the smooth completion of missions. Although the Wolf pack algorithm is fast and robust in trajectory planning, which has good results for solving problems with complex high dimensions and multiple peaks. In view of the premature convergence, the poor global optimization ability and the final result does not reach the optimal route of Wolf package algorithm (WPA), and the slow convergence of genetic algorithm, an improved trajectory planning method is proposed. First, the equivalent terrain simulation method is used to equivalent and analyze the terrain obstacles in the working environment with the mountains, and constructed the equivalent terrain map of the work of UAV. Planning known UAV orbit at the beginning and end positions, simulations in matlab found that the improved Wolf pack algorithm can find the shortest path with shorter time. Eventually, our simulation results are better than using the Wolf Pack Algorithm or the Genetic Algorithm.

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Autonomous Inspection Method of UHV Substation Robot Based on Deep Learning in Cloud Computing Environment

Wang,

Meng,

Zhao

2023

J CIRCUIT SYST COMP

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Aiming at the problem that substation robots cannot automatically find and analyze the fault equipment and carry out patrol inspection, a method of autonomous patrol inspection for ultra-high voltage (UHV) substation robots based on deep learning in cloud computing environment is proposed. Firstly, based on the cloud computing environment, an autonomous patrol system is designed to upload the data obtained by robots to the cloud platform for processing, so as to complete data analysis quickly and with high quality. Then, the deep learning algorithm (DL) is used for fault diagnosis, and the FP-growth algorithm is combined to realize the association mining of fault data, so as to clarify the patrol order of fault-related nodes. Finally, the improved ant colony algorithm (IAC) is used to optimize the path of the robot to complete the reliable inspection of the substation in the shortest time. Based on the selected UHV substation, the experimental analysis of the proposed method shows that the fault diagnosis error rate and time are about 4.3% and 14.2[Formula: see text]s, respectively, and the patrol path is only 180.351[Formula: see text]m, and the patrol time is 19.708[Formula: see text]s, which can realize the optimal patrol of the robot.

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Robot navigation path planning in power plant based on improved wolf pack algorithm

Cited by 4 publications

References 3 publications

Implementation of PID controller and enhanced red deer algorithm in optimal path planning of substation inspection robots

Implementation of PID controller and enhanced red deer algorithm in optimal path planning of substation inspection robots

UAV Path Planning Method Based on Improved Wolf Pack Algorithm

Autonomous Inspection Method of UHV Substation Robot Based on Deep Learning in Cloud Computing Environment

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