Autonomous Landing at Unprepared Sites for a Cargo Unmanned Air System

Award Information
Agency:
Department of Defense
Branch
Navy
Amount:
$69,999.00
Award Year:
2010
Program:
STTR
Phase:
Phase I
Contract:
N00014-10-M-0365
Award Id:
95171
Agency Tracking Number:
N10A-039-0101
Solicitation Year:
n/a
Solicitation Topic Code:
NAVY 10T039
Solicitation Number:
n/a
Small Business Information
986 Cragmont Ave, Berkeley, CA, 94708
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
807504410
Principal Investigator:
VasonSrini
Executive Director
(510) 527-7183
srini@datafluxsystems.com
Business Contact:
VasonSrini
Executive Director
(510) 527-7183
srini@datafluxsystems.com
Research Institute:
University of California
Deirdre McAuliffe-Bauer
BWRC
2108 Allston Way
Berkeley, CA, 94704
(510) 666-3100

Abstract
We propose to design, develop, implement, simulate, and demonstrate an autonomous control and sensing system for the safe vertical landing of autonomous aerial cargo delivery system (ACDS). The landing site is expected to be unprepared mountain sides with slopes up to 15 degrees and rough terrain containing rocks and brush. We also plan to reduce the amount of ground equipment required to operate the system, overall weight and power requirements of the control and sensing system, and estimate probability of hard landing. During Phase I we will develop two approaches for sensing systems using FMCW radar and 3D Flash Ladar in selecting the landing site from a distance of 75 m and estimate the cost, weight, volume, computing requirement for processing raw sensor data and running control algorithms, and the total power needed for sensors and computers. We will also simulate the control and sensing algorithms on the RIPTIDE environment using the vehicle dynamics model of Yamaha RMAX and Boeing's A160T. We will develop metrics to evaluate the performance of the control algorithms and sensing approaches and provide an initial set of results using the simulation environment. During Phase II we will perform a detailed implementation of the control algorithms and sensing approaches. We will simulate performance using 6-degree of freedom models for RMAX and Boeing's A160T and tune the control algorithm and sensing approaches. At the end of Phase II we will do a demonstration of landing using the RMAX on a hill side.

* information listed above is at the time of submission.

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