摘要
利用无人机对观测目标的运动轨迹进行预测是当前无人系统领域的关键任务之一。目前的目标轨迹预测研究通常基于单一无人机所采集的轨迹数据,但由于场景中障碍物以及视角倾斜等因素的影响,单无人机不易稳定监测目标具体位置,容易导致目标丢失。而且,现有利用无人机的目标轨迹预测一般基于鸟瞰视角,没有发挥出无人机的灵活性。随着无人机集群协同技术的发展,无人机群体视角为目标全方位监测提供了新的思路,在解决目标丢失和目标遮挡问题中具有明显的优势。同时,基于多无人机的位姿估计可以估计出目标的准确三维坐标,为无人机的灵活视角观测提供基础。因此,从轨迹预测的相关工作出发,探讨无人机群体视角下轨迹预测中面临的挑战和解决思路,以期对未来的轨迹预测研究以及集群协同技术发展提供一定帮助。
Trajectory prediction is a key task in unmanned systems. Current research on the trajectory prediction is based on the trajectory dataset collected by a single device, commonly by UAV. Due to the influence of obstacles and occlusion in the scene, it is difficult to determine the specific location of the target in complex scene and tends to lose the target. In the meantime, current works in trajectory prediction observed by UAV usually rely on a bird’s-eye view(BEV), which restricts the flexibility of UAV. The development of group collaboration technology brings new opportunities to overcome these limitations of single UAV. From the group perspective, UAVs can effectively solve the problems of target occlusion and target localization. In the meantime, the pose estimation based on UAV group can compute the accurate 3 D location of targets and provide a basis for feasible observation of the scene. In this paper, starting from the related work of trajectory prediction from the group perspective, we aim to present the new topic of trajectory prediction from UAV group perspective and discuss the challenges and solutions of this field, and provide some potential insights for the trajectory prediction research.
作者
房建武
李旭阳
杜凯
薛建儒
FANG Jian-wu;LI Xu-yang;DU Kai;XUE Jian-ru(College of Transportation Engineering,Chang'an University,Xi'an 710061,China;College of Electronic and Control Engineering,Chang'an University,Xi'an 710061,China;College of Artificial Intelligence,Xi'an Jiaotong University,Xi'an 710061,China)
出处
《导航定位与授时》
CSCD
2022年第5期15-27,共13页
Navigation Positioning and Timing
基金
国家自然科学重点基金(62036008)
基础加强计划技术领域(2021-JCJQ-JJ-0004)。
关键词
轨迹预测
群体视角
无人机
深度学习
集群协同
Trajectory prediction
Group perspective
UAV
Deep learning
Group collaboration