CAJ | 학술논문

针对蚁群算法路径规划初期信息素浓度差异较小，正反馈作用不明显，路径搜索存在着盲目性、收敛速度相对较慢、易陷入局部最优等情况，人工势场算法的势场力可引导机器人快速朝目标位置前进，提出势场蚁群算法，通过栅格法对机器人的工作环境进行建模，利用人工势场中的势场力、势场力启发信息影响系数及蚁群算法中机器人与目标位置的距离构造综合启发信息，并利用蚁群算法的搜索机制在未知环境中寻找一条最优路径。大量的仿真实验表明势场蚁群算法路径规划能找到更优路径和收敛速度更快。
침대의군산법로경규화초기신식소농도차이교소，정반궤작용불명현，로경수색존재착맹목성、수렴속도상대교만、역함입국부최우등정황，인공세장산법적세장력가인도궤기인쾌속조목표위치전진，제출세장의군산법，통과책격법대궤기인적공작배경진행건모，이용인공세장중적세장력、세장력계발신식영향계수급의군산법중궤기인여목표위치적거리구조종합계발신식，병이용의군산법적수색궤제재미지배경중심조일조최우로경。대량적방진실험표명세장의군산법로경규화능조도경우로경화수렴속도경쾌。
In view of the shortcomings of traditional ant colony algorithm are searching unreasonable, the converge slowly and getting into local solutions easily for the differential concentration of pheromone is small and the positive feedback have not obvious effect. The potential force of artificial potential field algorithm can guide the robot to the goal position, a kind of ant colony optimization with potential field heuristic, modeling the environment with grid method, the potential force, the potential force-influence coefficient and the distance between the robot and the goal are utilized to construct comprehensive heuristic information, ant colony algorithm mechanism is used to search a path in an unknown environment, many simulation results show ant colony optimization with potential field heuristic can find a shorter path and the con-verges fast.