Detection of screws on metal-ceiling structures for dismantling tasks in buildings

Abstract

In the renewal process of office interiors, a robotic system is needed in order to assist the human workers engaged in this kind of job. Regarding the items in the ceiling side, after the dismantling task of the ceiling panels, it is necessary to remove carefully the screws that once held these boards to the Light Gauge Steel (LGS), with the purpose of reusing. The proposed methodology to achieve the task consists at first of the LGS detection. Such detection is useful as a first approach to detect the screws because a trajectory under and near of that metal-ceiling structure can be generated for a scanning process. In both tasks, a stereo camera configured as an eye-in-hand system is necessary. During the motion under the structure, the screws are detected by applying a multi-template matching process to every caught image. A multi-frame integration increases the robustness in the screw detection process. The results of all the processed images along the trajectory are analyzed in order to measure both the true and the false positive detection rates of the screws attached to the LGS and to measure the 3D position of each one.

DCNN-Based Screw Detection for Automated Disassembly Processes

“…Most of these were either too much model-dependent; meaning screw-specific (i.e. only Torx8) or device-specific (i.e., only electric motor screws) [9], [12] or they were extremely brittle due to the fact that the methods they used were highly dependent on classical computer vision methods, which are easily affected by a slight change of illumination [13]. Also, unlike methods like [9], we do not require a depth sensor (i.e., RGB-D camera) to conduct the detection.…”

An intelligent detection approach for end-of-life power battery shell bolts

“…However, due to the unique structure of motors, their algorithm cannot be directly applied to other fields. Similarly, Cruz-Ramirez et al 16 utilized a visual system combined with lighting feedback to detect and disassemble ceiling bolts, but this approach requires assistance from robots and specialized lighting systems. Other methods efficiently recognize bolt heads but require bolt movement.…”

A Bolt Assembly Robotic System Based on Hybrid Vision: Effect of its Process Parameters on Fastening Performance

“…Therefore, robot vision and the human eyes have similar principles and functions. They acquire [12,13], process, and analyze images to provide a feedback signal to the robot. The combination of robots and vision guidance technology [14] can improve robots' automatic and intelligent operation levels.…”