Depth Evaluation from Pattern Projection Optimized for Automated Electronics Assembling Robots
| Autor: | Jong-Rul Park, Jun-Dong Cho |
|---|---|
| Rok vydání: | 2014 |
| Předmět: |
Computer science
business.industry ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Process (computing) Object (computer science) Object detection law.invention Projector law Computer graphics (images) Signal Processing Robot Computer vision Artificial intelligence Electrical and Electronic Engineering Projection (set theory) business Robotic arm Structured light |
| Zdroj: | IEIE Transactions on Smart Processing and Computing. 3:195-204 |
| ISSN: | 2287-5255 |
| DOI: | 10.5573/ieiespc.2014.3.4.195 |
| Popis: | This paper presents the depth evaluation for object detection by automated assembling robots. Pattern distortion analysis from a structured light system identifies an object with the greatest depth from its background. An automated assembling robot should prior select and pick an object with the greatest depth to reduce the physical harm during the picking action of the robot arm. Object detection is then combined with a depth evaluation to provide contour, showing the edges of an object with the greatest depth. The contour provides shape information to an automated assembling robot, which equips the laser based proxy sensor, for picking up and placing an object in the intended place. The depth evaluation process using structured light for an automated electronics assembling robot is accelerated for an image frame to be used for computation using the simplest experimental set, which consists of a single camera and projector. The experiments for the depth evaluation process required 31 ms to 32 ms, which were optimized for the robot vision system that equips a 30-frames-per-second camera. |
| Databáze: | OpenAIRE |
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