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Selection of inspection path optimization scheme based on analytic hierarchy process and inspection experimental study

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Abstract

This paper mainly studies the optimization of the patrol route of a fire inspection robot, based on analytic hierarchy process (AHP) and fire source detection. First, the A* algorithm is improved based on two aspects of the heuristic function and of the obstacle boundary setting, while the suboptimal path is obtained in MATLAB. Next, the path planned according to the improved A* algorithm is smoothed and optimized, by means of gradient descent method, Bezier curve and B-spline curve, while the index parameters are optimized by means of MATLAB simulation. In view of the simulation results, the trajectory optimization performance index evaluation system, established by five decision criteria, including running time, path length, ride comfort, no-collision effect and quadratic optimization space, is put forward. The three kinds of optimization methods are analyzed qualitatively and quantitatively, and the results show that, in the total hierarchical ranking, the B-spline curve trajectory optimization scheme has the largest weight and is more important than the other two schemes. Finally, the superiority of B-spline curve is verified experimentally.

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Acknowledgments

This work is supported by the Project of Hebei International Science and technology cooperation base construction (No. 19391825D), the financial support of National Natural Science Foundation of China (No. U2037202) and Postgraduate Innovation Subsidy Project of Hebei Province (No. CXZZBS2021134).

Author information

Authors and Affiliations

  1. Parallel Robot Mechatronic System Laboratory, Hebei Province, Yanshan University, Qinhuangdao, 066004, China

    Shuo Zhang, Jiantao Yao, Ruochao Wang, Yu Tian, Jiaxin Wang & Yongsheng Zhao

  2. School of Mechanical Engineering, Yanshan University, Qinhuangdao, 066004, China

    Shuo Zhang, Jiantao Yao, Yu Tian, Jiaxin Wang & Yongsheng Zhao

  3. Key Laboratory of Advanced Forging & Stamping Technology and Science, Ministry of Education, Yanshan University, Qinhuangdao, 066004, China

    Jiantao Yao & Yongsheng Zhao

  4. Intelligent Robotics Institute, School of Mechatronical Engineering, Beijing Institute of Technology, Beijing, 100081, China

    Ruochao Wang

Authors
  1. Shuo Zhang
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  2. Jiantao Yao
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  3. Ruochao Wang
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  4. Yu Tian
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  5. Jiaxin Wang
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  6. Yongsheng Zhao
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Corresponding author

Correspondence to Jiantao Yao.

Additional information

Shuo Zhang is currently pursuing the Ph.D. degree in mechatronics engineering from the Yanshan University, Qinhuangdao, China. He received the B.S. degree in mechanical engineering from the School of Mechanical Engineering, Yanshan University, Qinhuangdao, China, in 2017. His research interests include intelligent fire-fighting robot design and application, and intelligent robot control.

Jiantao Yao, corresponding author, is currently a Professor of the School of Mechanical Engineering, and Parallel Robot and Mechatronic System Laboratory of Hebei Province, Yanshan University. He received the Ph.D. degree in mechanical and electronic engineering from Yanshan University, Hebei, China, in 2009. His current research interests include soft robotics, force and torque sensors, parallel mechanisms, and their application in the field of heavy machinery and intelligent robots.

Ruochao Wang is currently pursuing the Ph.D. degree in Intelligent Robotics Institute, School of Mechatronical Engineering, Beijing Institute of Technology, Beijing, China. He received the M.S. degree in mechanical and electronic engineering from Yanshan University, Hebei, China, in 2020. His current research interests is intelligent robots.

Yu Tian is currently pursuing the M.S. degree in mechanical and electronic engineering at Yanshan University. She received the B.S. degree in mechanical engineering from the School of Mechanical Engineering, Yanshan University, Qinhuangdao, China, in 2018. Her research interest is intelligent fire-fighting robot design and application.

Jiaxin Wang is currently pursuing the M.S. degree in mechanical and electronic engineering at Yanshan University. He received the B.S. degree in mechanical engineering from the School of Mechanical Engineering, Yanshan University, Qinhuangdao, China, in 2021. His research interest is intelligent fire-fighting robot design and application.

Yongsheng Zhao is currently the Vice-President of Yanshan University. He received the Ph.D. degree in mechanical engineering from Yanshan University, Hebei, China, in 1999. Since then, he has been a Professor with the Robotics Research Center, Yanshan University. His current research interests include parallel mechanisms, force and torque sensors, advanced manufacturing technique, and intelligent robots.

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Zhang, S., Yao, J., Wang, R. et al. Selection of inspection path optimization scheme based on analytic hierarchy process and inspection experimental study. J Mech Sci Technol 37, 355–366 (2023). https://doi.org/10.1007/s12206-022-1234-z

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  • DOI: https://doi.org/10.1007/s12206-022-1234-z

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