基于视觉的多机器人协作SLAM 问题

 视觉SLAM 仅采用图像作为外部信息,用于估计机器人位置的同时构建环境地图。SLAM 是机器人自主性的基本前提,如今在小动态环境采用激光或者声呐传感器构建2D 地图得到较好地解决。然而动态、复杂和大范围下的SLAM 仍存在问题,使用视觉作为基本的外部传感器是解决问题的一个新颖热门的研究方法。在视觉SLAM 中使用计算机视觉技术,如特征检测、特征描述和特征匹配,图像识别和恢复,还存在很多改善的空间。本文在视觉SLAM 领域的最新技术的基础上,对基于视觉的多机器人协作SLAM 领域的前沿技术进行综述。

A survey on the cooperative SLAM problem of multi-robots systems based on visual

Visual SLAM using only images as external information estimates the robot position while building the environment map. SLAM is a basic prerequisite for autonomous robots. Now it has been solved by using a laser or sonar sensor to build 2D map in a small dynamic environment. However, in a dynamic, wide range and complex environment there are still problems to be solved, and the use of vision as the basic external sensor is a new area of research. The use of computer vision techniques in visual SLAM, such as feature detection, characterization, feature matching, image recognition and recovery, has still much room for improvement. The paper offers a brief overview on visual SLAM about the latest and easy to understand technologies in the field. Multi-robot systems have many advantages over a single robot, which can improve the precision of SLAM system, and better adapt to the dynamic and complex environment. This paper expounds the methods of multi-robot SLAM, with emphasis on the map fusion methods.