张宁 Fast and Robust Initialization for Visual-Inertial SLAM
链接：https://pan.baidu.com/s/1cdkuHdkSi9x7l-96zMbX7g 提取码：b3ff
Carlos Campos, Jos´e M.M. Montiel and Juan D. Tard´os
Visual-inertial SLAM (VI-SLAM) requires a good initial estimation of the initial velocity, orientation with respect to gravity and gyroscope and accelerometer biases.In this paper we build on the initialization method proposed by Martinelli [1] and extended by Kaiser et al. [2], modifying it to be more general and efficient. We improve accuracy with several rounds of visual-inertial bundle adjustment, and robustify the method with novel observability and consensus tests, that discard erroneous solutions. Our results on the EuRoC dataset show that, while the original method produces scale errors up to 156%, our method is able to consistently initialize in less than two seconds with scale errors around 5%, which can be further reduced to less than 1% performing visual-inertial bundle adjustment after ten seconds.
视觉惯性SLAM（VI-SLAM）需要对初始速度，相对于重力和陀螺仪的方向以及加速度计偏差进行良好的初始估计。在本文中，我们建立了Martinelli提出的初始化方法[1]并由Kaiser等人[2]扩展，将其修改为更一般和更有效。我们通过几轮视觉惯性束调整来提高准确性，并通过新颖的可观察性和共识测试来证明该方法，从而丢弃错误的解决方案。我们在EuRoC数据集上的结果表明，虽然原始方法产生的标度误差高达156％，但我们的方法能够在不到两秒的时间内始终如一地进行初始化，标度误差约为5％，视觉惯性束调整进行十秒钟后可进一步降低至小于1％。