受限空间自适应区域栅格化的优化路径规划

针对障碍物分布复杂、存在封闭边界的受限空间,提出一种环境自适应区域栅格化的优化路径规划算法.该算法首先将环境自适应划分为区域栅格,并提出阻碍度指标降低搜索空间的维度以优化区域栅格的划分;然后结合随机变异和定向变异,给出一种可有效平衡搜索效率与精度矛盾的多维变异粒子群优化算法;最后使用最小二乘曲线拟合方法对优化路径予以平滑处理.与非线性递减惯性权值粒子群算法（NDW-PSO）及组合粒子群算法（C-PSO）对比的仿真结果验证了所提出算法的先进性.

Optimal path planning in limited space based on adaptive regional grid

Aiming at the limited space with complex obstacle distribution and closed boundary,an optimal path planning algorithm based on adaptive regional grid is presented.Firstly,the environment is divided into regional grid adaptively,and a measure is proposed to optimize the division of regional grid,which is used to reduce the dimension of search space and defined as block degree.Afterwards,an improved particle swarm optimization(PSO) algorithm combined with random mutation operator and directional mutation operator is proposed.Finally,the least-square curve fitting method is used to smooth the optimal path.Simulation results show the superiority of improved PSO algorithm by comparing with nonlinearly decreasing weight PSO(NDW-PSO) algorithm and composite PSO(C-PSO) algorithm.