Abstract
Modern developments in electronics, electric motors, and automatic control have contributed to making quadcopters cheap, easily accessible, and with a wide range of use. In this work, a model predictive controller for a quadcopter is developed for tracking a moving object within the field-of-view (FOV) of a camera mounted on the quadcopter. A mathematical representation of the quadcopter is presented with the help of quaternions, whereas the tracked object is modeled as a car. The FOV is defined with the help of a pinhole camera model and represents a nonlinear constraint within the MPC design. Not only is a desired point in space kept within the camera's FOV but also as close as possible to its principal axis. The method is tested in different scenarios of varying complexity. The results are evaluated in terms of flight quality, constraint compliance, and computation effort and demonstrate the potential of the concept to stabilize the quadcopter and track the desired object within the camera's FOV.
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