论文标题
用于搜索和跟踪的概率无线电视觉感应
Probabilistic Radio-Visual Active Sensing for Search and Tracking
论文作者
论文摘要
积极的搜索和跟踪搜索和救援任务或协作移动机器人技术取决于传感平台来检测和本地化目标。在本文中，我们专注于通过配备有无线电接收器和相机的空中机器人来视觉检测发射目标。基于视觉的跟踪可提供高精度，但是感应域的方向性可能需要较长的搜索时间，然后才能检测到目标。相反，无线电信号具有较大的覆盖范围，但跟踪准确性较低。因此，我们设计了一种递归的贝叶斯估计方案，该方案使用摄像头观测来完善无线电测量。为了调节摄像头姿势，我们设计了一个最佳控制器，其成本函数是在概率地图上构建的。理论结果支持所提出的算法，而数值分析在视觉和仅放射线基线方面显示出更高的鲁棒性和效率。
Active Search and Tracking for search and rescue missions or collaborative mobile robotics relies on the actuation of a sensing platform to detect and localize a target. In this paper we focus on visually detecting a radio-emitting target with an aerial robot equipped with a radio receiver and a camera. Visual-based tracking provides high accuracy, but the directionality of the sensing domain may require long search times before detecting the target. Conversely, radio signals have larger coverage, but lower tracking accuracy. Thus, we design a Recursive Bayesian Estimation scheme that uses camera observations to refine radio measurements. To regulate the camera pose, we design an optimal controller whose cost function is built upon a probabilistic map. Theoretical results support the proposed algorithm, while numerical analyses show higher robustness and efficiency with respect to visual and radio-only baselines.
