A System Combining Force and Vision Sensing for Automated Screw Removal on Laptops
This brief investigates the performance of an automated robotic system, which uses a combination of vision and force sensing to remove screws from the back of laptops. This robotic system uses two webcams, one that is fixed over the robot and the other mounted on the robot, as well as a sensor-equip...
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Veröffentlicht in: | IEEE transactions on automation science and engineering 2018-04, Vol.15 (2), p.887-895 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | This brief investigates the performance of an automated robotic system, which uses a combination of vision and force sensing to remove screws from the back of laptops. This robotic system uses two webcams, one that is fixed over the robot and the other mounted on the robot, as well as a sensor-equipped (SE) screwdriver. Experimental studies were conducted to test the performance of the SE screwdriver and vision system. The parameters that were varied included the internal brightness settings on the webcams, the method in which the workspace was illuminated, and color of the laptop case. A localized light source and higher brightness setting as the laptop's case became darker produced the best results. In this brief, the SE screwdriver was able to successfully remove 96.5% of the screws.
Note to Practitioners -The amount of discarded electronic waste (e-waste) is increasing rapidly, yet efficient, nondestructive, automated methods to handle the waste have not been developed. Many e-waste products such as laptops use fasteners that need to be removed. In this brief, we focus on removing screws from laptops in a nondestructive manner in order to not damage the laptop, so its parts can be recycled. Due to the vast amounts of laptop models, it is necessary to create a method that will automatically recognize the locations of these fasteners. This brief presents a prototype robotic system that integrates force and vision sensing to automatically locate and remove screws from various models of laptops. The methodology presented in this brief is applicable to other e-waste products with a casing attached by screws. A current limitation of this brief is the robotic system that has to investigate all potential hole locations found by the vision system, although some of these locations may not correspond to valid screw locations. This brief can be extended to include a memory feature that will remember the locations of the screws for cases with similar laptops that are handled by the system to improve the processing time. |
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ISSN: | 1545-5955 1558-3783 |
DOI: | 10.1109/TASE.2017.2679720 |