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The first step for any robot to achieve true autonomy is to create a map of its surroundings and localize itself within this map at the same time. This is popularly known as the Simultaneous Localization and Mapping (SLAM) problem. Although much theory has been developed over the years to solve the SLAM problem, researchers have been having difficulties in real-world application. This is because sensors and actuators onboard a robot are always corrupted by noise. In particular, Unmanned Aerial Vehicles (UAVs) face additional difficulties that land vehicles do not. Because UAVs travel in 3D rather than 2D, additional nonlinearities associated with rotation complicate the SLAM solution. Furthermore, excessive vibration during flight can render sensitive onboard sensors useless. TO BE CONT’D
James Forbes
Duowen Qian
ARA Robotique
Engineering - mechanical
Aerospace and defense
Accelerate
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