基于改进麻雀算法的配电房巡检机器人路径规划

Path planning of inspection robot in distribution room based on improved sparrow search algorithm

针对麻雀算法在路径规划中出现的效率低、耗时长等问题,提出了一种改进的麻雀算法用于配电房巡检机器人的路径规划。首先,利用Logistic-Tent混沌映射优化麻雀种群质量,减少后续的盲目搜索;其次,提出了可控自适应随机探索的发现者更新策略,增强算法全局搜索能力的同时进一步提高规划效率,缩短搜索时间;接着,为避免算法后期陷入停滞,引入螺旋位置更新因子,加强局部开发能力;最后,结合三次插值B样条进行平滑处理,使路径更适用于配电房环境。实验结果表明:改进的麻雀算法能够高效完成巡检时的路径规划任务,相比于原始算法在迭代效率、路径搜索时间等方面优化显著。

Aiming at the problems of low efficiency and long time consumption in path planning of sparrow algorithm,an improved sparrow algorithm is proposed for path planning of inspection robots in distribution rooms.Firstly,using Logistic Tent chaotic mapping to optimize the quality of sparrow population and reduce subsequent blind searches.Secondly,a controllable adaptive random exploration discoverer update strategy was proposed to enhance the algorithm′s global search capability while further improving planning efficiency and shortening search time.Next,in order to avoid algorithm stagnation in the later stage,a spiral position update factor is introduced to enhance local development capabilities.Finally,combining cubic interpolation B-splines for smoothing processing makes the path more suitable for the distribution room environment.The experimental results show that the improved sparrow algorithm can efficiently complete the path planning task during inspections.Compared to the original algorithm,it is significantly optimized in terms of iteration efficiency,path search time,and other aspects.