Title:
Self-Contained Autonomous Indoor Flight with Ranging Sensor Navigation
Self-Contained Autonomous Indoor Flight with Ranging Sensor Navigation
Author(s)
Chowdhary, Girish
Sobers, D. Michael, Jr.
Pravitra, Chintasid
Christmann, Hans Claus
Wu, Allen
Hashimoto, Hiroyuki
Ong, Chester
Kalghatgi, Roshan
Johnson, Eric N.
Sobers, D. Michael, Jr.
Pravitra, Chintasid
Christmann, Hans Claus
Wu, Allen
Hashimoto, Hiroyuki
Ong, Chester
Kalghatgi, Roshan
Johnson, Eric N.
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Abstract
This paper describes the design and flight test of a completely
self-contained autonomous indoor Miniature Unmanned Aerial System (M-UAS). Guidance, navigation, and control algorithms are presented, enabling the
M-UAS to autonomously explore cluttered indoor areas without relying on any
off-board computation or external navigation aids such as GPS. The system uses
a scanning laser rangefinder and a streamlined Simultaneous Localization and
Mapping (SLAM) algorithm to provide a position and heading estimate, which is
combined with other sensor data to form a six degree-of-freedom inertial
navigation solution. This enables an accurate estimate of the vehicle
attitude, relative position, and velocity. The state information, with a
self-generated map, is used to implement a frontier-based exhaustive search
of an indoor environment. Improvements to existing guidance algorithms
balance exploration with the need to remain within sensor range of indoor
structures such that the SLAM algorithm has sufficient information to form a
reliable position estimate. A dilution of precision metric is developed to quantify the effect of environment geometry on the SLAM pose covariance, which
is then used to update the 2-D position and heading in the navigation filter. Simulation and flight test results validate the presented algorithms.
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Date Issued
2012-11
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