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Pose estimation

State estimation for the path-Following of visual unmanned ground systems

An state estimator for the path-Following control problem of unmanned car-like visual systems was developed. This state estimator is composed by five modules each one with a different mission.

 

3D Reconstruction for Unmanned Aerial Vehicle

3D Reconstruction using SLAM (SFM) algorithms and Point Cloud Library for Unmanned Aerial Vehicle can establish the whole real-time unknown environment in Ground Station (GS), this research aims to construct the 3D environment for (Map-based) indoor applications and explore the SLAM (SFM) techniques to future UAV (6D) Monocular or Stereo Visual Odometry researches. (Pose Estimation)

3D Reconstruction

Vision-based pose estimation using 3D markers

Sometimes, UAVs fly in GPS-denied environments, where there is no easy way for them to determine their own pose, relative to their surroundings. This research line tries to address this problem using visual information from an onboard camera.