论文标题
向后导航和目标跟踪，以实行瞬态放射性检测
Receding Horizon Navigation and Target Tracking for Aerial Detection of Transient Radioactivity
论文作者
论文摘要
该论文为四型型\ ac {mav}介绍了一个退缩的地平线规划和控制策略，以导航并在混乱的未知和动态环境中拦截移动目标。利用轻巧的短距离传感器，该传感器在相对狭窄且短\ ac {fov}中产生点云，以及一个\ acs {ssd} -mobileNet基于基于MobileNet的深神经网络，在\ ac {Mav}上运行\ ac {Mav}，提议的运动计划和控制策略可安全，动态可行\ acveient \ acv ave \ acv ave \ acv trafience Inter \ ac av ave} \ acs {fov}，该车辆使用该车辆自动导航，追求和拦截其移动目标。此任务是完成的，而无需依赖全球规划师或有关环境或移动目标的事先信息。在混乱的室内和室外环境中，在数值和实验中证明了报告的计划者的有效性，最大速度高达4.5-5〜m/s。
The paper presents a receding horizon planning and control strategy for quadrotor-type \ac{mav}s to navigate reactively and intercept a moving target in a cluttered unknown and dynamic environment. Leveraging a lightweight short-range sensor that generates a point-cloud within a relatively narrow and short \ac{fov}, and an \acs{ssd}-MobileNet based Deep neural network running on board the \ac{mav}, the proposed motion planning and control strategy produces safe and dynamically feasible \ac{mav} trajectories within the sensor \acs{fov}, which the vehicle uses to autonomously navigate, pursue, and intercept its moving target. This task is completed without reliance on a global planner or prior information about the environment or the moving target. The effectiveness of the reported planner is demonstrated numerically and experimentally in cluttered indoor and outdoor environments featuring maximum speeds of up to 4.5-5~m/s.
