Abstract
To solve the disadvantages of the traditional lion swarm algorithm in power inspection path planning, such as parameter dependence, poor global optimization ability, prone to the premature phenomenon, and central tendency, an improved lion swarm algorithm was proposed. By exploring and developing an equilibrium factor <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\omega$</tex> , the position relationship of the lion group is more dependent on the number of populations and the number of iterations, jumping out of the local optimum, and significantly improving the global optimization of the algorithm. Finally, based on the MATLAB simulation platform, the grid environment model was constructed, and the optimal decision rules of electric power inspection robot walking were generated by the rough set theory. The traditional genetic algorithm, particle swarm optimization algorithm, lion swarm algorithm and improved lion swarm algorithm were used to find the optimal path. The simulation results showd that the improved lion swarm optimization algorithm has the shortest path length and the fastest iteration convergence speed, and it is efficient and economical for power inspection.
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