This paper describes an image based visual servoing (IBVS) system for a nonholonomic robot to achieve good trajectory following without real-time robot pose information and without a known visual map of the environment. We call it trajectory servoing. The critical component is a feature-based, indirect SLAM method to provide a pool of available features with estimated depth, so that they may be propagated forward in time to generate image feature trajectories for visual servoing. Short and long distance experiments show the benefits of trajectory servoing for navigating unknown areas without absolute positioning. Trajectory servoing is shown to be more accurate than pose-based feedback when both rely on the same underlying SLAM system.
翻译:本文描述了一种基于图像的视觉扫描系统(IBVS),用于一个非光学机器人,在没有实时机器人提供信息而且没有已知的环境视觉地图的情况下,实现良好的轨迹。我们称之为轨迹筛选。关键部件是一种基于地貌的间接 SLM 方法,以提供具有估计深度的现有特征库,从而可以及时向前传播,以生成视觉振荡的图像轨迹。短距离和长距离实验显示轨迹在没有绝对定位的情况下对未知区域进行导航的好处。如果两者都依赖相同的SLM 基本系统,轨迹筛选比基于表面的反馈更准确。