University of Twente Student Theses


Detection of objects and their orientation from 3D point clouds in an industrial robotics setting

Sredhar, Devi Darshana (2021) Detection of objects and their orientation from 3D point clouds in an industrial robotics setting.

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Abstract:Lidar techniques are highly suitable for employing in industrial setups such as in the automatic unloading of cargo containers. However, the restrictions on the sensor positions allow the cargo container to be scanned only from a certain position and angle. The varying point density in the point cloud data because of the scanning geometry affects the detection of individual instances of similar objects. Here, we study such a lidar system to detect and obtain the positions of the objects present in the scene to manipulate them. This research leverages the available information from single-shot lidar representations of open cargo containers stacked with box-like objects. The study uses a direct point cloud segmentation technique as the baseline method and explores an alternate approach by employing a projection-based point cloud segmentation method to find a solution. The problem of varying point density is handled by increasing the footprint of the laser points using a uniform kernel during the projection of point cloud data to an image. The projected point cloud data is then segmented using the watershed method to detect the number of objects. The study also compares the two segmentation methods – the segment growing method used for direct point cloud segmentation and the watershed method. The results are evaluated quantitatively and qualitatively. Furthermore, we obtain the object pose with six degrees of freedom and extract the object dimensions to be communicated to the robotic manipulator for unloading the container. With these properties, in future work, the objects could be identified in the real world.
Item Type:Essay (Master)
Faculty:ITC: Faculty of Geo-information Science and Earth Observation
Programme:Geoinformation Science and Earth Observation MSc (75014)
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