Abstract
This chapter brings a tutorial about use of Point Cloud data for the environment perception of mobile robots. Point Cloud is a powerful tool that gives robots the ability to perceive the world around them through a dense measurement. One advantage of this kind of sensor is the large measuring space, with faint or no external light. Although there are several works about Point Clouds, only a few of them speak about how this kind of information can be obtained and what can be extracted. This chapter aims to fill this gap and clarify how Point Clouds can be acquired, processed, transformed between coordinate systems and which these information can be easily extracted using ROS and Matlab. The codes used in this chapter are available in GitHub and can be found at https://github.com/air-lasca/ros_book_point_cloud. The videos developed with the experiments can be seen on YouTube, in Robot LASCA channel that can be accessed at https://www.youtube.com/channel/UCtgnBqaodQAGtbh0HW9nJEA.
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Teixeira, M.A.S., Santos, H.B., de Oliveira, A.S., Arruda, L.V., Neves, F. (2017). Robots Perception Through 3D Point Cloud Sensors. In: Koubaa, A. (eds) Robot Operating System (ROS). Studies in Computational Intelligence, vol 707. Springer, Cham. https://doi.org/10.1007/978-3-319-54927-9_16
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