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MSc Thesis N. Dijkshoorn
The small size of micro aerial vehicles (MAVs) allows a wide range of robotic applications, such as surveillance, inspection and search & rescue.
In order to operate autonomously, the robot requires the ability to known its position and movement in the environment.
Since no assumptions can be made about the environment, the robot has to learn from its environment.
Simultaneous Localization and Mapping (SLAM) using aerial vehicles is an active research area in robotics.
However, current approaches use algorithms that are computationally expensive and cannot be applied for realtime navigation problems.
Furthermore, most researchers rely on expensive aerial vehicles with advanced sensors.
This thesis presents a realtime SLAM approach for affordable MAVs with a down-looking camera.
Focusing on realtime methods and affordable MAVs increases the employability of aerial vehicles in real world situations.
The approach has been validated with the
