RaD-VIO: Rangefinder-aided Downward Visual-Inertial Odometry


State-of-the-art forward facing monocular visual-inertial odometry algorithms are often brittle in practice, especially whilst dealing with initialisation and motion in directions that render the state unobservable. In such cases having a reliable complementary odometry algorithm enables robust and resilient flight. Using the common local planarity assumption, we present a fast, dense, and direct frame-to-frame visual-inertial odometry algorithm for downward facing cameras that minimises a joint cost function involving a homography based photometric cost and an IMU regularisation term. Via extensive evaluation in a variety of scenarios we demonstrate superior performance than existing state-of-the-art downward facing odometry algorithms for Micro Aerial Vehicles (MAVs).



  • Bo Fu, Master Student, Mechanical Engineering Department

  • Kumar Shaurya Shankar, PhD Student, Robotics Institute

  • Nathan Michael, Associate Research Professor, Robotics Institute;



RaD-VIO: Rangefinder-aided Downward Visual-Inertial Odometry B Fu, KS Shankar, N Michael arXiv preprint arXiv:1810.08704