Status on Video Data Reduction and Air Delivery Payload Pose Estimation
Abstract
The paper discloses a current status of the development and evaluation of an autonomous payload tracking capability for determining time, state and attitude information (TSPI) for
all types of airdrop loads. This automated capability of accurately acquiring TSPI data is supposed to radically reduce the labor time and eliminate man-in-the-loop errors. The paper
starts with the problem formulation and then reviews the developed software. The algorithms rely on commercial off-the-shelf feature-based video-data processing software
adopted for obtaining TSPI. Having the frame coordinates of the centroid of a tracking item available from no less than three ground stationary surveyed cameras at each instant during
a descent together with these cameras azimuth and elevation information allows solving the position estimation problem. If more known-geometry features of the airdrop load can
reliably be extracted, the pose (position and attitude) estimation would also be possible. The paper primarily addresses the status of the payloadメs position estimation portion providing
examples of processing video data from up to six cameras. Yet, it also discusses the applicability of more recent computer-vision algorithm, based on establishing and tracking
multiple scale-invariant keypoints. The paper ends with conclusions and suggestions for the further development.
Description
19th AIAA Aerodynamic Decelerator Systems Technology Conference and Seminar, Williamsburg, VA, May 21-24, 2007.
Rights
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.Related items
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