摘要
为了寻找更优的机器人移动路径,将沙猫群优化算法与三次样条插值方法进行融合,对沙猫群优化算法进行改进。在改进的沙猫群优化算法中,利用混沌映射的均匀性初始化种群以提高种群多样性;通过融合互利共生和莱维飞行策略减少局部最优解的消极影响,提高算法的收敛速度和精度。通过两种仿真实验对比6种优化算法的实验数据,结果表明,改进的沙猫群优化算法的最优解、最差解和平均解都优于对比算法,验证了改进沙猫群优化算法对于解决移动机器人路径规划问题的有效性和工程实用性。
In order to find a better robot moving path,the sand cat swarm optimization algorithm was combined with the cubic spline interpolation method to improve the sand cat swarm optimization algorithm.In the improved sand cat swarm optimization algorithm,the uniformity of chaotic mapping was used to initialize the population to improve the population diversity.Secondly,by integrating mutualism and introducing Levy flight strategy,the negative impact of local optimal solution was reduced and the convergence speed and accuracy of the algorithm were improved.In two simulation experiments,the experimental data of the six optimization algorithms were compared.Results show that the optimal solution,the worst solution and the average solution of the improved sand cat swarm optimization algorithm were all better than those of the comparison algorithm,which verifies the effectiveness and engineering practicability of the improved sand cat swarm optimization algorithm for solving the path planning problem of mobile robots.
作者
贾鹤鸣
李永超
游进华
李政邦
饶洪华
文昌盛
JIA Heming;LI Yongchao;YOU Jinhua;LI Zhengbang;RAO Honghua;WEN Changsheng(Department of Information Engineering,Sanming University,Sanming 365004,China;School of Computer Science and Mathematics,Fujian University of Technology,Fuzhou 350118,China)
出处
《福建工程学院学报》
CAS
2023年第1期72-77,共6页
Journal of Fujian University of Technology
基金
福建省自然科学基金面上项目(2021J011128)。
关键词
机器人路径规划
沙猫群优化算法
三次样条插值
混沌映射
互利共生
莱维飞行
robot path planning
sand cat swarm optimization algorithm
cubic spline interpolation
chaotic mapping
mutual symbiosis
Levy flight
