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A novel visual-inertial Monocular SLAM

机译：新型视觉惯性单眼SLAM

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With the development of sensors and computer vision research community, cameras, which are accurate, compact, well-understood and most importantly cheap and ubiquitous today, have gradually been at the center of robot location. Simultaneous localization and mapping (SLAM) using visual features, which is a system getting motion information from image acquisition equipment and rebuild the structure in unknown environment. We provide an analysis of bio-inspired flights in insects, employing a novel technique based on SLAM. Then combining visual and inertial measurements to get high accuracy and robustness, we present a novel tightly-coupled Visual-inertial Simultaneous Localization and Mapping system which get a new attempt to address two challenges which are the initialization problem and the calibration problem, experimental results and analysis show the proposed approach has a more accurate quantitative simulation of insect navigation, which can reach the positioning accuracy of centimeter level.
机译：随着传感器和计算机视觉研究社区的发展，精确，紧凑，易于理解，最重要的是廉价和无处不在的摄像头已逐渐成为机器人定位的中心。使用视觉功能的同时定位和制图（SLAM），这是一个从图像采集设备获取运动信息并在未知环境中重建结构的系统。我们使用基于SLAM的新技术，对昆虫中受生物启发的飞行进行了分析。然后结合视觉和惯性测量以获得高精度和鲁棒性，我们提出了一种新型的紧密耦合的视觉惯性同时定位和制图系统，它试图解决初始化问题和校准问题，实验结果和分析表明，该方法对昆虫导航具有更精确的定量模拟，可以达到厘米级的定位精度。

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