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Detekcija gibanja robota s 3D kamero
ID VOVK, DOMEN (Author), ID Munih, Marko (Mentor) More about this mentor... This link opens in a new window, ID Pogačnik, Luka (Comentor)

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Abstract
Diplomsko delo obravnava sledenje robotu z uporabo oblaka točk in določanje kotov v sklepih robota. Sestavili smo sistem z LIDAR-jem in robotom ter napisali program, ki je sposoben slediti premikom robota. Z globinsko kamero smo med izvajanjem robotskega programa zajemali oblake točk in nanje z algoritmom iterativne najbližje točke prilegali modela dveh glavnih robotskih segmentov. Kote v oseh robota smo določili na podlagi transformacijskih matrik, ki jih je algoritem vrnil. Testirali smo vplive različnih hitrosti izvajanja robotskega programa in preverili dva različna položaja kamere glede na robota. Ugotovili smo, da poravnava deluje tako pri počasnih kot hitrejših premikih robota. Program daje slabe rezultate le v primeru, ko LIDAR ne vidi ustreznih segmentov robota.

Language:Slovenian
Keywords:Globinski vid, iterativna najbližja točka, oblak točk, detekcija robota
Work type:Bachelor thesis/paper
Organization:FE - Faculty of Electrical Engineering
Year:2022
PID:20.500.12556/RUL-139998 This link opens in a new window
COBISS.SI-ID:120455683 This link opens in a new window
Publication date in RUL:09.09.2022
Views:1000
Downloads:48
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Secondary language

Language:English
Title:Robot motion detection with a 3D camera
Abstract:
The thesis deals with robot tracking using a point cloud and calculation of the robot's joint angles. We assembled a system with a LIDAR and a robot and created a program capable of robot tracking. While the robot was moving, a point cloud was repeatedly captured by the depth camera. Using the iterative closest point algorithm, we could then align the models of the two main segments of the robot with the captured point cloud. The joint angles were calculated using the transformation matrix returned by the algorithm. We tested our program with different speeds of the robot and two different camera positions. The experimental results show that the software functions properly with slow robot movements and gives good resuts with higher speeds as well. Errors occur when the segments cannot be seen by the LIDAR.

Keywords:Depth vision, iterative closest point, point cloud, robot detection

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