Autonomous navigation algorithm for precision landing on unknown planetary surfaces
Year: 2008
Type: article
Abstract: A localization algorithm is developed to assist automated landing on unknown plan-etary surface. Classically, using a vision-sensor only, the vehicle states are subject to an observability issue. In order to overcome this problem, relative motion estimates were used as measurements in addition to image-plane data of the feature points. Us-ing these data as measurements, a nonlinear least square estimator was designed that estimates the state vector when a priori knowledge of the state is not available. Fur-thermore, an Extended Kalman filter with fusing on-board IMU data was developed and shows promising results for future refinement of the previous estimates.
Authors: Baro Hyun, Puneet Singla
Institution: University at Buffalo, State University of New York
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W2602110321