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  • Michal Jama, Co-Major Professor, Balasubramaniam Natarajan, Dale Schinstock
  • 2011
In this dissertation, two applications related to vision-based localization and mapping are considered: (1) improving navigation system based satellite location estimates by using on-board camera images, and (2) deriving position information from video stream and using it to aid an auto-pilot of an unmanned aerial vehicle (UAV). In the first part of this(More)
Low cost unmanned aerial systems (UAS) have great potential for rapid proximal measurements of plants in agriculture. In the context of plant breeding and genetics, current approaches for phenotyping a large number of breeding lines under field conditions require substantial investments in time, cost, and labor. For field-based high-throughput phenotyping(More)
—This paper describes a recent and very advantageous upgrade of the undergraduate controls laboratory in the Mechanical and Nuclear Engineering Department at Kansas State University. The current lab has been in use for about a decade. Details regarding the original hardware fundamental to the laboratory activities, including the embedded digital signal(More)
In this paper, a novel method is presented for tracking ground targets from an unmanned aerial vehicle (UAV) outfitted with a single monocular camera. The loss of observability resulting from the use of a single monocular camera is dealt with by constraining the target vehicle to follow ground terrain. An unscented Kalman filter (UKF) provides a(More)
The core objective of this research is to develop an estimator capable of tracking the states of ground targets with observation measurements obtained from a single monocular camera mounted on a small unmanned aerial vehicle (UAV). Typical sensors on a small UAV include an inertial measurement unit (IMU) with three axes accelerometer and rate gyro sensors(More)
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