Tyler Ryan

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In this paper we describe a vision-based algorithm to control a vertical-takeoff-and-landing unmanned aerial vehicle while tracking and landing on a moving platform. Specifically, we use image-based visual servoing (IBVS) to track the platform in two-dimensional image space and generate a velocity reference command used as the input to an adaptive sliding(More)
In this paper, we present a method for using linear matrix inequalities (LMIs) to synthesize controller gains for a quadrotor system. The controller is based on approximate feedback linearization and is structured to allow for tuning similar to proportional-integral-derivative (PID) controllers. The synthesis procedure generates suboptimal gains with(More)
In this paper, we describe a method for using Bayesian inference to create probabilistic point correspondences in video sequences. Using state prior distribution information from the onboard Kalman filter found in most unmanned aerial vehicles, we derive an accurate normal approximation for the movement of points in image space. It is then a direct(More)
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