Campos Ricard, Gracias Nuno, Ridao Pere
Computer Vision and Robotics, University of Girona, Girona 17071, Spain.
Sensors (Basel). 2016 Mar 17;16(3):387. doi: 10.3390/s16030387.
Multi-robot formations are an important advance in recent robotic developments, as they allow a group of robots to merge their capacities and perform surveys in a more convenient way. With the aim of keeping the costs and acoustic communications to a minimum, cooperative navigation of multiple underwater vehicles is usually performed at the control level. In order to maintain the desired formation, individual robots just react to simple control directives extracted from range measurements or ultra-short baseline (USBL) systems. Thus, the robots are unaware of their global positioning, which presents a problem for the further processing of the collected data. The aim of this paper is two-fold. First, we present a global alignment method to correct the dead reckoning trajectories of multiple vehicles to resemble the paths followed during the mission using the acoustic messages passed between vehicles. Second, we focus on the optical mapping application of these types of formations and extend the optimization framework to allow for multi-vehicle geo-referenced optical 3D mapping using monocular cameras. The inclusion of optical constraints is not performed using the common bundle adjustment techniques, but in a form improving the computational efficiency of the resulting optimization problem and presenting a generic process to fuse optical reconstructions with navigation data. We show the performance of the proposed method on real datasets collected within the Morph EU-FP7 project.
多机器人编队是近年来机器人技术发展的一项重要进展,因为它们能使一组机器人整合各自的能力,以更便捷的方式进行勘测。为了将成本和声学通信降至最低,多水下航行器的协同导航通常在控制层面进行。为了维持所需的编队,单个机器人只需对从距离测量或超短基线(USBL)系统中提取的简单控制指令做出反应。因此,机器人并不知道它们的全球定位,这给所收集数据的进一步处理带来了问题。本文的目标有两个。首先,我们提出一种全局对齐方法,利用航行器之间传递的声学信息,校正多航行器的航位推算轨迹,使其类似于任务执行期间所遵循的路径。其次,我们专注于这类编队的光学测绘应用,并扩展优化框架,以允许使用单目相机进行多航行器地理参考光学三维测绘。光学约束的纳入并非使用常见的光束平差技术,而是以一种提高所得优化问题计算效率的形式,并呈现一种将光学重建与导航数据融合的通用过程。我们在Morph欧盟第七框架计划项目中收集的真实数据集上展示了所提方法的性能。