Department of Computer Science, CUCEI, University of Guadalajara, Av. Revolución 1500 Modulo "O" Col. Olimpica, Guadalajara 44830, Jalisco, Mexico.
Sensors (Basel). 2013 Jul 3;13(7):8501-22. doi: 10.3390/s130708501.
Simultaneous localization and mapping (SLAM) is an important problem to solve in robotics theory in order to build truly autonomous mobile robots. This work presents a novel method for implementing a SLAM system based on a single camera sensor. The SLAM with a single camera, or monocular SLAM, is probably one of the most complex SLAM variants. In this case, a single camera, which is freely moving through its environment, represents the sole sensor input to the system. The sensors have a large impact on the algorithm used for SLAM. Cameras are used more frequently, because they provide a lot of information and are well adapted for embedded systems: they are light, cheap and power-saving. Nevertheless, and unlike range sensors, which provide range and angular information, a camera is a projective sensor providing only angular measurements of image features. Therefore, depth information (range) cannot be obtained in a single step. In this case, special techniques for feature system-initialization are needed in order to enable the use of angular sensors (as cameras) in SLAM systems. The main contribution of this work is to present a novel and robust scheme for incorporating and measuring visual features in filtering-based monocular SLAM systems. The proposed method is based in a two-step technique, which is intended to exploit all the information available in angular measurements. Unlike previous schemes, the values of parameters used by the initialization technique are derived directly from the sensor characteristics, thus simplifying the tuning of the system. The experimental results show that the proposed method surpasses the performance of previous schemes.
同时定位与建图（SLAM）是机器人理论中一个重要的问题，目的是构建真正自主的移动机器人。本工作提出了一种基于单目相机传感器实现 SLAM 系统的新方法。单目相机 SLAM（或简称单目 SLAM）可能是最复杂的 SLAM 变体之一。在这种情况下，一个自由移动的单目相机是系统唯一的传感器输入。传感器对 SLAM 所使用的算法有很大的影响。相机被更频繁地使用，因为它们提供了大量的信息，并且非常适合嵌入式系统：它们轻便、便宜且省电。然而，与提供距离和角度信息的距离传感器不同，相机是一种投影传感器，只能提供图像特征的角度测量值。因此，无法在单个步骤中获得深度信息（距离）。在这种情况下，需要特殊的特征系统初始化技术，以便在 SLAM 系统中使用角度传感器（如相机）。本工作的主要贡献是提出了一种新的、鲁棒的方案，用于在基于滤波的单目 SLAM 系统中融合和测量视觉特征。所提出的方法基于两步技术，旨在利用角度测量中提供的所有信息。与之前的方案不同，初始化技术使用的参数值直接从传感器特性中推导出来，从而简化了系统的调整。实验结果表明，所提出的方法优于之前的方案。
