Power inspection is crucial to ensure a stable power system. Manual inspection is time-consuming and prone to errors, so intelligent methods like machine inspection greatly improve efficiency and accuracy. However, machine inspection faces challenges in path planning due to unexpected situations. To address this, a hybrid path planning algorithm that combines improved ant colony and dynamic window methods is proposed. Implemented in a power inspection robot dog, the algorithm enhances inspection efficiency. Simulation results demonstrate its advantages in both single-task and multi-task global path planning, reducing path length, turning nodes, iterations, and running time. Local path planning experiments show successful obstacle avoidance. The practical application of the robot dog confirms its ability to navigate around basic and complex obstacles. Overall, the proposed method has good applicability to power inspection robot dog’s path planning and navigation.

[1] Amaike H., Fukuhara A., Kano T., and Ishiguro A., “Decentralized Control Mechanism for Limb Steering in Quadruped Robot Walking,” Advanced Robotics, vol. 38, no. 16, pp. 1124-1140, 2024. DOI:10.1080/01691864.2024.2376030

[2] Bingol M. and Aydogmus O., “Performing Predefined Tasks Using the Human-Robot Interaction On Speech Recognition for an Industrial Robot,” Engineering Applications of Artificial Intelligence, vol. 95, pp. 103903, 2020. https://doi.org/10.1016/j.engappai.2020.103903

[3] Chen K. and Tsui C., “The Fuzzy Control Approach for a Quadruped Robot Guide Dog,” International Journal of Fuzzy Systems, vol. 23, pp. 1789-1796, 2021. https://doi.org/10.1007/s40815-020-01046-x

[4] Chen Q., Chen Y., Zhu J., Luca G., Zhang M., and Guo Y., “Traffic Light and Moving Object Detection for a Guide-Dog Robot,” in Proceedings of the 3rd Asian Conference on Artificial Intelligence Technology, Chongqing, pp. 675-678, 2019. https://doi.org/10.1049/joe.2019.1137

[5] Chen Y. and Luca G., “Technologies Supporting Artificial Intelligence and Robotics Application Development,” Technologies Supporting Artificial Intelligence and Robotics Application Development, vol. 1, no. 1, pp. 1-8, 2021. https://doi.org/10.37965/jait.2020.0065

[6] Cheng L., Chang L., Song Y., Wang H., and Bian Y., “A Robot Path Planning Method based on Synergy Behavior of Cockroach Colony,” The International Arab Journal on Information Technology, vol. 20, no. 5, pp. 717-726, 2023. https://doi.org/10.34028/iajit/20/5/4

[7] Chung H., Maharjan S., Zhang Y., Eliassen F., and Strunz K., “Placement and Routing Optimization for Automated Inspection with Unmanned Aerial Vehicles: A Study in Offshore Wind Farm,” IEEE Transactions on Industrial Informatics, vol. 17, no. 5, pp. 3032-3043, 2021. https://doi.org/10.1109/TII.2020.3004816

[8] Fu J., Núñez A., and De Schutter B., “Real-Time UAV Routing Strategy for Monitoring and Inspection for Postdisaster Restoration of Distribution Networks,” IEEE Transactions on Industrial Informatics, vol. 18, no. 4, pp. 2582- 2592, 2022. https://doi.org/10.1109/TII.2021.3098506

[9] Higurashi Y., Hattori Y., and Wada N., “Head and Trunk Rotation in Roll during Turning in Agility Dogs,” Mammal Study, vol. 49, no. 2, pp. 125-135, 2024. DOI:10.3106/ms2023-0021

[10] Hong B., Lin Z., Chen X., Hou J., Lv S., and Gao Z., “Development and Application of Key Technologies for Guide Dog Robot: A Systematic Literature Review,” Robotics and Autonomous Systems, vol. 154, pp. 104104, 2022. https://doi.org/10.1016/j.robot.2022.104104

[11] Jain K. and Saxena A., “Simulation on Supplier Side Bidding Strategy at Day-Ahead Electricity Market Using Ant Lion Optimizer,” Journal of Computational and Cognitive Engineering, vol. 2, no. 1, pp. 17-27, 2023. https://doi.org/10.47852/bonviewJCCE2202160

[12] Jiang X. and Deng Y., “UAV Track Planning of Electric Tower Pole Inspection Based on Improved Artificial Potential Field Method,” Journal of Applied Science and Engineering, vol. 24, no. 2, 123-132, 2021. https://doi.org/10.6180/jase.202104_24(2).0001

[13] Kim J., Chung D., Kim Y., and Kim H., “Deep Learning-Based 3D Reconstruction of Scaffolds Using a Robot Dog,” Automation in Construction, vol. 134, pp. 104092, 2022 https://doi.org/10.1016/j.autcon.2021.104092.

[14] Li J., Jin S., Wang C., Xue J., and Wang X., “Weld Line Recognition and Path Planning with Spherical Tank Inspection Robots,” Journal of Field Robot, vol. 39, pp. 131-152, 2022. https://doi.org/10.1002/rob.22042

[15] Liu J., Zhao T., and Dian S., “General Type-2 Fuzzy Sliding Mode Control for Motion Balance Adjusting of Power-Line Inspection Robot,” Soft Computing, vol. 25, pp. 1033-1047, 2021. https://doi.org/10.1007/s00500-020-05202-1

[16] Liu T., Kuang J., Ge W., Zhang P., and Niu X., “A Simple Positioning System for Large-Scale Indoor Patrol Inspection Using Foot-Mounted INS, QR Code Control Points, and Smartphone,” IEEE Sensors Journal, vol. 21, no. 4, pp. 4938-4948, 2021. https://doi.org/10.1109/JSEN.2020.3030934

[17] Luo Y., Yu X., Yang D., and Zhou B., “A Survey of Intelligent Transmission Line Inspection Based on Unmanned Aerial Vehicle,” Artificial Intelligence Review, vol. 56, pp. 173-201, 2023. https://doi.org/10.1007/s10462-022-10189-2

[18] Lv J., Yan L., Chu S., Cai Z., Pan J., He X., and Xue J., “A New Hybrid Algorithm Based on Golden Eagle Optimizer and Grey Wolf Optimizer for 3D Path Planning of Multiple UAVs in Power Inspection,” Neural Computing and Applications, vol. 34, pp. 11911-11936, 2022. https://doi.org/10.1007/s00521-022-07080-0

[19] Majumder A., Majumder A., and Bhaumik R., Power Inspection Robot Dog Inspection Line Planning and Autonomous Navigation Strategy 503 “Teaching-Learning-Based Optimization Algorithm for Path Planning and Task Allocation in Multi-Robot Plant Inspection System,” Arabian Journal for Science and Engineering, vol. 46, pp. 8999-9021, 2021. https://doi.org/10.1007/s13369- 021-05710-8

[20] Mirza N., “Robotic path planning and fuzzy neural networks,” The International Arab Journal on Information Technology, vol. 17, no. 4A, pp. 615- 620, 2020. https://doi.org/10.34028/iajit/17/4A/5

[21] Nagy B. and Korondi P., “Deep Learning-Based Recognition and Analysis of Limb-Independent Dog Behavior for Ethorobotical Application,” IEEE Access, vol. 10, pp. 3825-3834, 2022. DOI:10.1109/ACCESS.2022.3140513

[22] Nekovář F., Faigl J., and Saska M., “Multi-Tour Set Traveling Salesman Problem in Planning Power Transmission Line Inspection,” IEEE Robotics and Automation Letters, vol. 6, no. 4, pp. 6196-6203, 2021. DOI:10.1109/LRA.2021.3091695

[23] Pan J., Lv J., Yan L., Weng S., Chu S., and Xue J., “Golden Eagle Optimizer with Double Learning Strategies for 3D Path Planning of UAV in Power Inspection,” Mathematics and Computers in Simulation, vol. 193, pp. 509-532, 2022. https://doi.org/10.1016/j.matcom.2021.10.032.

[24] Santos C., Abdali M., Martins D., and Alexandre C., “Geometrical Motion Planning for Cable- Climbing Robots Applied to Distribution Power Lines Inspection,” International Journal of Systems Science, vol. 52, no, 8, pp. 1646-1663, 2021. https://doi.org/10.1080/00207721.2020.1868612

[25] Shao H., Zhao Q., Chen B., Liu X., and Feng Z., “Analysis of Position and State Estimation of Quadruped Robot Dog Based on Invariant Extended Kalman Filter,” International Journal of Robotics and Automation Technology, vol. 9, pp. 17-25, 2022. https://doi.org/10.31875/2409- 9694.2022.09.03

[26] Song L., Wang H., and Chen P., “Automatic Patrol and Inspection Method for Machinery Diagnosis Robot-Sound Signal-Based Fuzzy Search Approach,” IEEE Sensors Journal, vol. 20, no. 15, pp. 8276-8286, 2020. https://doi.org/10.1109/JSEN.2020.2978396.

[27] Wu D., “Overview of the Development History and Current Design Status of Quadrupedal Animal Robots,” Journal of Artificial Intelligence Practice, vol. 7, no. 2, pp. 161-165, 2024. DOI:10.23977/jaip.2024.070221

[28] Zan J., “Research on Robot Path Perception and Optimization Technology Based on Whale Optimization Algorithm,” Journal of Computational and Cognitive Engineering, vol. 1, no. 4, pp. 201-208, 2022. https://doi.org/10.47852/bonviewJCCE59782020 5514

[29] Zhang W., Huang R., and Ye L., “Evaluation of Emission Reduction Performance of Power Enterprises Based on Least Squares Support Vector Machine,” The International Arab Journal of Information Technology, vol. 21, no. 5, pp. 854- 865, 2024. https://doi.org/10.34028/iajit/21/5/7

[30] Zheng H., Hongxing W., Tianpei Z., and Bin Y., “The Collaborative Power Inspection Task Allocation Method of “Unmanned Aerial Vehicle and Operating Vehicle,” IEEE Access, vol. 9, pp. 62926-62934, 2021. DOI:10.1109/ACCESS.2021.3074710 Bingye Zhang, June 1981, female, Han, Linhai City, Zhejiang Province, with a bachelor's degree in Computer Science and Engineering from Shanghai Electric Power University in 2003. Work experience: From 2003 to 2019, worked as a technical specialist at State Grid Taizhou Power Supply Company. From 2020 to 2023, served as the Director and Deputy Manager of the Information and Communication Technology Department of the Technology Branch of Taizhou Hongchuang Power Group Co., Ltd. Academic situation: Responsible for winning the first prize of Zhejiang Electric Power Company's Science and Technology Innovation Award for the project, obtaining 2 invention patents and 1 utility model patent, and publishing papers such as “Research on Intelligent Power Outage Management in Distribution Network under Major Maintenance Mode” and “Research on a Video Quality Intelligent Detection System”. 504 The International Arab Journal of Information Technology, Vol. 22, No. 3, May 2025 Minjie Zhu, born in Wenzhou City, Zhejiang Province, in July 1972. He obtained a Bachelor's degree in Electrical Engineering and Automation from Shanghai Electric Power University in 2004 and a Master's degree in Electrical Engineering from Zhejiang University in 2012, specializing in power planning and construction. Work experience: From 2013 to 2020, served as the Director of the Construction Department and General Manager Assistant of State Grid Zhejiang Electric Power Supply Company. From 2020 to 2023, served as the Deputy General Manager and Party Committee Member of State Grid Zhejiang Electric Power Supply Company Taizhou Branch. Academic situation: The first author obtained 1 invention patent and 2 utility model patents; Mainly participated in 4 invention patents and 5 utility model patents; In terms of papers, he has successively published one Chinese core journal as the first author and three journals included in EI; In terms of monographs, as a member of the editorial committee, I wrote four monographs. Haibo Li, born in May 1983 in Taizhou City, Zhejiang Province, China. He obtained a Bachelor's degree in Automation from Chongqing University in 2005 and a Master's degree in Electrical Engineering from Chongqing University in 2010, with a research direction in Power Systems and Automation. Work experience: From 2010 to 2013, worked as a full-time employee at the Transmission and Inspection Center of State Grid Taizhou Power Supply Company. From 2014 to 2018, worked as a full-time employee at the Human Resources Department of State Grid Taizhou Power Supply Company. From 2018 to 2021, worked as the Deputy Director of the Transmission and Inspection Center of State Grid Taizhou Power Supply Company. From 2023 to present, worked as the Party Branch Secretary and Deputy Manager of the Technology Branch of Taizhou Hongchuang Power Group Co., Ltd. Academic situation: Served as the leader of a technology project twice, applied for 2 invention patents, published 4 Chinese core and EI papers on the project, and Studied new power Systems and Artificial Intelligence. Hongliang Zou, born in Gao'an City, Jiangxi Province, China in June 1982, majoring in new power systems and artificial intelligence. Bachelor's degree in Electronic Information Engineering from Wuhan University in 2004. 2007 Master's degree in Power Electronics and Power Transmission from Wuhan University. PhD in Power System and Automation from Wuhan University in 2017.Work experience: From 2012 to 2017, worked as a specialist in the maintenance and repair of switches, transformers, and substations in the operation and maintenance department. From 2017 to 2020, Deputy Director of the Operations and Maintenance Department (in charge of power transformation and planning). From 2020 to 2021, Deputy Director of the Internet Office. From 2021 to present, Manager of Hongchuang Group Technology Branch Four invention patents have been granted in the fields of artificial intelligence and power energy, published a total of 6 papers in the field of power technology, including 3 IE conference papers, 1 electrical technology paper, and 2 high-voltage technology papers. Xueyan Wang, born in December 1994 in Taizhou City, Zhejiang Province, China, holds a Master's degree in Electrical Engineering from Hunan University in June 2020. Work experience: From September 2029 to present, an employee of the Production and Research Department of the Technology Branch of Taizhou Hongchuang Power Group Co., Ltd. Academic situation: Served as a technology project leader 5 times, applied for over 50 invention patents, authorized over 20 invention patents, published 4 high-level journal papers, and completed 2 enterprise level gold medal product releases.