ICUAS'17 Paper Abstract


Paper ThA5.2

Ringkowski, Michael (University of Kansas), Chao, Haiyang (University of Kansas)

State Estimation Using Inertial Optical Flows for a Fixed-Wing UAS

Scheduled for presentation during the "Sensor Fusion - I" (ThA5), Thursday, June 15, 2017, 10:20−10:40, San Marco Island

2017 International Conference on Unmanned Aircraft Systems, June 13-16, 2017, Miami Marriott Biscayne Bay, Miami, FL,

This information is tentative and subject to change. Compiled on April 12, 2021

Keywords Navigation, Sensor Fusion, Micro- and Mini- UAS


Autonomous navigation and obstacle avoidance in complex terrains such as canyons or urban/indoor environments is one of the biggest challenges for the next generation of unmanned aircraft systems. Insects such as honeybees use optical flow for various navigation tasks. Similar strategies can be used by unmanned aircraft as well. More importantly, optical flow can be combined with inertial measurements to achieve state estimation such as ground velocity and terrain shape. In this paper, a new state estimation algorithm is proposed for the estimation of ground speed and simple terrain shape using inertial optical flows. Epipolar constraints are combined with optical flow motion of equation for robust state estimation. Simulation results show the effectiveness of the proposed algorithm.



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