Real-Time Robust Stereo Visual SLAM System Based on Bionic Eyes
Real-Time Robust Stereo Visual SLAM System Based on Bionic Eyes
复制标题
基于仿生眼的实时鲁棒立体视觉SLAM系统
DOI：
10.1109/tmrb.2020.3011981
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发表时间：
2020-08-01
期刊：
影响因子：
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通讯作者：
Zhang, Xiaolin
中科院分区：
文献类型：
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作者：
Liu, Yanqing;Zhu, Dongchen;Zhang, Xiaolin
视觉同步定位与测绘(SLAM)系统可获得摄像机的精确自我运动和环境的3D表示。虽然SLAM系统在许多常见场景中的性能令人印象深刻，但跟踪失败仍然是一个非常具有挑战性的问题，在低纹理环境和相机快速运动的情况下总是存在的。本文提出了一种基于仿生眼的实时立体视觉SLAM系统。这种名为仿生眼的新型传感器基本上是立体摄像机，可以执行人眼的所有动作。我们的系统很好地结合了传感器和算法。为了找到更多的特征点，我们提出了一种仿生眼睛的自主搜索策略，该策略主要是受人眼的边缘视觉和中枢视觉的启发。之后，使用一种稳健的运动估计方法计算摄像机运动。我们的系统在室内低纹理和大规模的室外环境中进行了测试。实验结果表明，与固定的立体摄像机相比，我们的仿生眼睛SLAM系统在面对低纹理环境时获得了更好的鲁棒性，避免了跟踪失败的问题。
Visual Simultaneously Localization and Mapping (SLAM) systems obtain accurate ego-motion of cameras and 3D representation of the environment. Although the performance of SLAM systems is very impressive in many common scenes, tracking failure is still a very challenging issue, which always exist in low-textured environment and rapid camera motion situations. In this paper, we propose a real-time stereo visual SLAM system using bionic eyes. The new type sensor named bionic eyes are basically the stereo cameras and perform all the movements of human eyes. Our system makes a good combination of sensors and algorithms. In order to find more feature points, we proposed an autonomous searching strategy of the bionic eyes, which is mainly inspired by the peripheral and central visual of human eyes. After that the camera motion is calculated using a robust motion estimation method. Our system is tested in indoor low-textured and large-scale outdoor environment. Experimental results show that compared to fixed stereo cameras, our bionic eyes SLAM system gains more robustness and avoid tracking failure problem when facing the low-textured environment.