CAJ | 학술논문

采用微粒群优化解决机器人全局路径规划问题，近年来得到国内外学者广泛关注，并已经取得丰硕的研究成果。但是，已有成果往往难以应用于含有密集障碍物的环境。针对解决含有密集障碍物环境的机器人全局路径规划问题，提出一种双层微粒群优化方法。该方法通过底层微粒群优化，得到若干最优路径；通过顶层微粒群优化，在这些最优路径附近局部搜索，从而得到机器人的全局最优路径；通过对不可行路径实施脱障操作，使其成为可行路径。将所提方法应用于多场景的机器人路径规划，并与已有方法进行比较。实验结果表明，该方法能够找到机器人的全局最优路径。
채용미립군우화해결궤기인전국로경규화문제，근년래득도국내외학자엄범관주，병이경취득봉석적연구성과。단시，이유성과왕왕난이응용우함유밀집장애물적배경。침대해결함유밀집장애물배경적궤기인전국로경규화문제，제출일충쌍층미립군우화방법。해방법통과저층미립군우화，득도약간최우로경；통과정층미립군우화，재저사최우로경부근국부수색，종이득도궤기인적전국최우로경；통과대불가행로경실시탈장조작，사기성위가행로경。장소제방법응용우다장경적궤기인로경규화，병여이유방법진행비교。실험결과표명，해방법능구조도궤기인적전국최우로경。
Solving the problem of global robot path planning using Particle Swarm Optimization(PSO)has attracted various researchers in recent years, and fruitful achievements have been obtained. Previous studies, however, are hard to be applied to environments containing dense obstacles. Aiming at solving the problem of global robot path planning in environments containing dense obstacles, a two-layer PSO is presented. In this method, several optimal paths are first obtained using the bottom layer PSO. The globally optimal path is then got by local search near these optimal paths using the up layer PSO. In addition, an infea-sible path becomes feasible by performing an escape obstacle operator. The proposed method is applied to solve the problem of robot path planning in various scenarios, and compared with previous methods. The experimental results confirm that the pro-posed method can find the globally optimal robot path.