Biometric measurement, calculation, and robot control are self-taught through repetitive learning. Optimized for Korea’s pig farming with weight variances between 60-150 kg.
Atypical Biometric Machine Vision Deep Learning AI
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Acquires LIDAR scan data of atypical biometrics
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Converts acquired data into 3D models for associative use
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Develops core formulas for anatomical biometric control through [ machine deep learning ]
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Generates coordinates for robot control
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Repetitive learning for robot control
Biometric Data Collection
4,000 new datasets collected daily
Cumulative Biometric Data in Deep Learning
Over 3 million datasets
Self-Developed AI Model for atypical Learning
ROBOS AI
Slaughterhouse Automation Robots
Automation Solutions for a Safe and Efficient Work Environment
The nature of the meat slaughtering industry presents many challenges for workers, both physically and psychologically. Workers face repetitive tasks in hazardous environments with risks of accidents, poor ventilation in the by-product rooms, drainage issues, and having to work in poor sanitary floor are part of the daily reality for slaughterhouse workers. Such harsh conditions and dangerous tasks need urgent improvement.
To address these issues, ROBOS has developed the “Atypical Biometric AI Assessment." In slaughterhouses, handling carcasses of various sizes and shapes (60kg to 150kg) requires precise calaculations of the positions. Our atypical biometric AI system utilizes LIDAR Vision and OpenCV-based object detection technology to analyze vision data of carcasses. With our own developed hardware and software technology, we ensure high precision and accuracy in delivering carcasses repetitively and effectively.
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Meat Processing Automation
Automated Smart Factory Solution for Pig and Cattle Slaughtering and Meat Processing
Despite many customers having automated their facilities, they still require numerous workers, which reduces efficiency. Errors in judgment of carcass information due to worker’s mistakes can lower product quality and reliability. Additionally, repetitive tasks increase the fatigue level of workers and rising occupational risk leading to musculoskeletal disorders.
To solve these problems, ROBOS uses its vision system and robots to accurately and quickly sort and pack materials. This automation system reduces the number of packaging workers from 5 to 2, cutting labor costs and increasing efficiency. By minimizing worker errors, we improve product quality and trustworthiness, and reduce the management burden caused by frequent employee turnover. ROBOS’ meat processing automation project is designed to make work environments safer and more efficient.