针对仿生扑翼微型飞行器飞行过程中的动态避障问题，提出了一种全局静态路径规划与局部动态路径规划相结合的避障路径规划策略。首先，综合考虑仿生扑翼微型飞行器的性能及其飞行环境，定义了路径规划的约束条件和代价函数，构建了全局静态避障的综合代价模型；其次，在此基础上考虑了动态障碍对其飞行性能的影响，提出基于时间窗口的碰撞约束，建立了融合局部动态避障规划的综合代价模型；最后，提出了改进蚁群算法，对综合全局静态路径规划与局部动态路径规划的避障路径规划进行优化求解。结果表明：本文综合动态避障路径规划策略可以有效地解决仿生扑翼微型飞行器在先验地图下的动态避障问题，一定程度上改进了动态障碍物下的避障路径寻优的不足；本文改进蚁群算法提升了动态路径寻优效率，保证了仿生扑翼微型飞行器避障控制的实时性要求。

Aiming at the dynamic obstacle avoidance problem during the flying process of the Flapping-wing Micro Air Vehicle （FWMAV）， a novel obstacle avoidance scheduling strategy integrating the global path planning and the locally dynamic path planning is proposed in this paper. The static comprehensive cost model is first built by considering both the performance constraints of the FWMAV and its threat constraints during the flight environment. Based on the static cost model， a time-varying collision constraint between the FWMAV and dynamic obstacles is defined and then the dynamic comprehensive cost model for the local obstacle avoidance is established. The improved ant colony algorithm is proposed for the obstacle avoidance scheduling strategy optimization. The results show that the proposed method can effectively handle the dynamic obstacle avoidance scheduling problem of the FWMAV under the known map and improve the dynamic obstacle avoidance scheduling strategy under the dynamic obstacles； meanwhile the improved ant colony algorithm can promote the efficiency of the dynamic path optimization to ensure the real-time requirement of the obstacle avoidance control of the FWMAV.