Unmanned Aerial Vehicle Navigation Using Wide-Field Optical Flow and Inertial Sensors

Matthew B. Rhudy, Yu Gu, Haiyang Chao, Jason N. Gross

Research output: Contribution to journalArticlepeer-review

19 Scopus citations


This paper offers a set of novel navigation techniques that rely on the use of inertial sensors and wide-field optical flow information. The aircraft ground velocity and attitude states are estimated with an Unscented Information Filter (UIF) and are evaluated with respect to two sets of experimental flight data collected from an Unmanned Aerial Vehicle (UAV). Two different formulations are proposed, a full state formulation including velocity and attitude and a simplified formulation which assumes that the lateral and vertical velocity of the aircraft are negligible. An additional state is also considered within each formulation to recover the image distance which can be measured using a laser rangefinder. The results demonstrate that the full state formulation is able to estimate the aircraft ground velocity to within 1.3 m/s of a GPS receiver solution used as reference "truth" and regulate attitude angles within 1.4 degrees standard deviation of error for both sets of flight data.

Original languageEnglish (US)
Article number251379
JournalJournal of Robotics
StatePublished - 2015

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • General Computer Science


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