Research on Path Planning of Power Operation Robot Based on Improved SMA Method
DOI:
https://doi.org/10.13052/dgaej2156-3306.4036Keywords:
PWLCM chaotic mapping, adaptive mutually beneficial symbiosis strategy, convex lens imaging strategy, power operation robot, path planningAbstract
To address the limitations of the slime mould algorithm (SMA) in power operation robot path planning, such as long path lengths, excessive search time, and uneven paths, this paper proposed an improved SMA, which called as ISMA. Firstly, PWLCM chaotic mapping is utilized to generate the population, enhancing its heterogeneity. Next, an adaptive mutually beneficial symbiosis strategy is introduced to refine the slime mould’s location update process, balancing global search and local exploitation. Finally, a convex lens imaging strategy is adopted to improve position updates, helping the algorithm escape local optima. When evaluating path length, operation time, and safety rate, the proposed ISMA outperforms both the ACO and classical SMA by achieving shorter path lengths and fewer collisions.
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