Machine Visual Location Method Research in Robot Unstacking

Li, Jinquan; Cui, Fang; Guan, Qi; Zhang, Rui

doi:10.12783/dtcse/cmee2016/5303

Cited by 1 publication

(1 citation statement)

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“…[2] Although this method of depalletization is fast, it lacks flexibility and accuracy, which becomes evident when faced with complex environments. [3] In recent years, researchers have integrated sensors into teach-in programmed robots for detection purposes to enhance their precision. One effective method of addressing these issues is the combination of vision and robot motion.…”

Section: Introductionmentioning

confidence: 99%

Design and implementation of robot depalletizing system based on 3D vision

Guo,

Jing,

2024

Fourth International Conference on Sensors and Information Technology (ICSI 2024)

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In response to the limitations of traditional industrial robots, which can only perform fixed-point palletizing tasks with low actual gripping accuracy and high failure rates, a 3D vision-based robot palletizing system was designed. This system focuses on the pallets containing workpieces and installs the camera in a manner similar to having eyes in the hands. To improve the robot's gripping accuracy, the Shape-NCC (Normalized Cross-Correlation) rotation-invariant template matching algorithm is used to identify target images, overcoming the problem of the traditional NCC algorithm being unable to find targets after image rotation. Using depth images, the system obtains the three-dimensional coordinates and rotation angles of the pallets in the target images, and communicates this position information to the robot via TCP. The robot then adjusts its grip position based on this information and ultimately completes the palletizing task automatically according to the palletizing strategy. Field experiments demonstrate that the system can achieve highprecision palletizing, with position errors within ±5mm and angle errors within ±1.7°. When operating at the highest speed in automatic mode, the palletizing speed reaches 70%, meeting the precision and speed requirements of industrial palletizing systems.

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Section: Introductionmentioning

confidence: 99%