基于三维视觉的避障模型
On a three dimensional vision based collision avoidance model
AI总结：
本文提出一种三维避障方法，通过生物群体协调行为启发，使无人机群在避开彼此和移动障碍物的同时汇聚至共同目标点。模型通过调整相对方位角和高度角调整速度向量，并满足个体感知限制。
摘要：
本文提出了一种基于三维视觉的避障方法，灵感来自生物群体中的协调行为。该方法旨在使无人机群能够收敛到共同目标点，同时避免彼此和环境中的移动障碍物碰撞。交互规则通过修改相对方位角和相对高度角来调整智能体的速度向量。此外，该模型满足由于个体感知灵敏度导致的有限视野约束。从所提出的个体基于模型中推导出平均场动力学模型。通过仿真验证了所提模型的有效性。
英文摘要：
This paper presents a three dimensional collision avoidance approach for aerial vehicles inspired by coordinated behaviors in biological groups. The proposed strategy aims to enable a group of vehicles to converge to a common destination point avoiding collisions with each other and with moving obstacles in their environment. The interaction rules lead the agents to adapt their velocity vectors through a modification of the relative bearing angle and the relative elevation. Moreover the model satisfies the limited field of view constraints resulting from individual perception sensitivity. From the proposed individual based model, a mean-field kinetic model is derived. Simulations are performed to show the effectiveness of the proposed model.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
