Combining visual and inertial measurements has become popular in mobile robotics, since the two sensing modalities offer complementary characteristics that make them the ideal choice for accurate Visual-Inertial Odometry or Simultaneous Localization
Abstract— In this paper, we present a monocular visual-inertial odometry algorithm which, by directly using pixel intensity errors of image patches, achieves accurate tracking performance while exhibiting a very high level of robustness. After detec
In this paper, we focus on the problem of motion tracking in unknown environments using visual and inertial sensors.We term this estimation task visual-inertial odometry (VIO), in analogy to the well-known visual-odometry problem. We present a detai
Abstract— In this paper, we develop a low-cost stereo visualinertial localization system, which leverages efficient multistate constraint Kalman filter (MSCKF)-based visual-inertial odometry (VIO) while utilizing an a priori LiDAR map to provide bou
Combining visual and inertial measurements has become popular in mobile robotics, since the two sensing modalities
offer complementary characteristics that make them the ideal choice for accurate Visual-Inertial Odometry or Simultaneous
Localization
Abstract: Current approaches for visual-inertial odometry
(VIO) are able to attain highly accurate state estimation via
nonlinear optimization. However, real-time optimization quickly
becomes infeasible as the trajectory grows over time; this prob
