System for object identification and localization using point clouds, developed by Alexander Ganslandt and Andreas Svensson as a master's thesis at the Institute of Computer Science at the Faculty of Engineering, Lund University. For details look at our master's thesis report.
This system identifies and localizes arbitrary objects using point clouds from a depth camera. It is intended for applications in robotics where the depth camera is mounted on a robot arm and positional data from the robot is used to merge point clouds. The system suggests where to move the camera to gain as much information as possible about the object, based on Next Best View heuristics. New objects to be identified/localized are easily added as CAD-models.
Installation instructions for Linux can be found here. Note that this project requires several special dependencies listed in the installation instructions.
An overview of the different parts of the system, as well as how to compile and use them can be found here.
Copyright 2018 Alexander Ganslandt and Andreas Svensson
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