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International Journal of Advanced Computer Science and Applications(IJACSA), Volume 15 Issue 10, 2024.
Abstract: As an indispensable energy source in production and daily life, electricity has important implications in the operation of society and economic development. As the hub of power transmission, the safety of transmission lines is related to the stability of the power grid. Regular inspection of transmission lines is an effective measure to ensure the stability of the power system. Patrol robots are used for regular inspection of transmission lines due to their advantages such as low cost and long running time. To achieve collision free, the study proposes an obstacle path planning algorithm based on an improved bidirectional fast expanding random tree through kinematic analysis of the robot. According to the experimental results, when overtaking the damper, the rotation ranges of the 1st claw/arm and the 2nd bracket/arm/claw were (0°~22°), (-50°, 10°), (0°, 25°), (-50°, 10°), and (0°, 22°), respectively. The corresponding rotational speeds were (-1.5~1.5) deg/s, (-3, 2.5) deg/s, (-3.5~3.5) deg/s, (-2.5, 3) deg/s, and (-27, 2) deg/s, respectively. The expansion and contraction ranges of the upper, middle, lower, and horizontal push rods were (0, 100) mm, (0, 110) mm, (-60, 10) mm, and (0, 20) mm, respectively. From the above results, when crossing obstacles, the motion acceleration of the inspection robot is not significant. The speed changes smoothly. The obstacle crossing path planning algorithm proposed in the study can achieve stable motion of the inspection robot.
Qianli Wang, “Simulation Analysis of Obstacle Crossing Stability for Transmission Line Inspection Robot” International Journal of Advanced Computer Science and Applications(IJACSA), 15(10), 2024. http://dx.doi.org/10.14569/IJACSA.2024.0151087
@article{Wang2024,
title = {Simulation Analysis of Obstacle Crossing Stability for Transmission Line Inspection Robot},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2024.0151087},
url = {http://dx.doi.org/10.14569/IJACSA.2024.0151087},
year = {2024},
publisher = {The Science and Information Organization},
volume = {15},
number = {10},
author = {Qianli Wang}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.