YOODS Unveils AI-Powered 3D Vision Sensors for High-Gloss Surface Recognition
YOODS Inc. announces new 3D vision sensors, the YCAM3DM and YCAM3D, designed to overcome automation challenges for reflective and metallic objects using integrated AI technology.
📋 Article Processing Timeline
- 📰 Published: May 27, 2026 at 22:43
- 🔍 Collected: May 27, 2026 at 14:00
- 🤖 AI Analyzed: May 27, 2026 at 14:00 (0 min after Collected)
YOODS Inc., a specialist in machine vision, has developed a new 3D vision system that successfully captures spatial data from glossy and mirrored surfaces—a long-standing hurdle in robotic automation. The lineup includes the wide-field 'YCAM3DM' and the lightweight 'YCAM3D' models.
Traditional 3D vision systems often fail with reflective materials, such as polished metal or glossy packaging, because light does not return predictably to the sensor. This technological gap has historically necessitated manual labor for handling metallic parts and reflective boxes. By combining proprietary image processing with AI, YOODS enables stable recognition of the position and orientation of high-reflection workpieces. This advancement allows robots to perform tasks such as picking, material handling, and depalletizing in previously un-automatable environments.
The system is scheduled for its public debut at "ROBOT TECHNOLOGY JAPAN 2026" (RTJ2026) from June 11 to 13, 2026, at Aichi Sky Expo. The exhibition will feature two primary demonstrations:
1. Recognition of High-Reflection Metal Parts (Wheels): Achieving high-precision tracking and masterless operation by utilizing cylindrical geometric features.
2. Glossy Object Depalletizing System: A robot-led solution for identifying and sorting silver boxes and bags, incorporating sequence control and size determination for practical industrial use.
YOODS aims to expand the boundaries of robotic capabilities by providing the necessary "eyes" and "brains" for complex manufacturing sites.
Traditional 3D vision systems often fail with reflective materials, such as polished metal or glossy packaging, because light does not return predictably to the sensor. This technological gap has historically necessitated manual labor for handling metallic parts and reflective boxes. By combining proprietary image processing with AI, YOODS enables stable recognition of the position and orientation of high-reflection workpieces. This advancement allows robots to perform tasks such as picking, material handling, and depalletizing in previously un-automatable environments.
The system is scheduled for its public debut at "ROBOT TECHNOLOGY JAPAN 2026" (RTJ2026) from June 11 to 13, 2026, at Aichi Sky Expo. The exhibition will feature two primary demonstrations:
1. Recognition of High-Reflection Metal Parts (Wheels): Achieving high-precision tracking and masterless operation by utilizing cylindrical geometric features.
2. Glossy Object Depalletizing System: A robot-led solution for identifying and sorting silver boxes and bags, incorporating sequence control and size determination for practical industrial use.
YOODS aims to expand the boundaries of robotic capabilities by providing the necessary "eyes" and "brains" for complex manufacturing sites.
FAQ
Why has 3D vision traditionally struggled with glossy objects?
Conventional sensors rely on light reflection patterns. Mirrored or highly reflective surfaces scatter or reflect light in ways that prevent the camera from accurately calculating depth and position.
What specific functions does the depalletizing system include?
Beyond simple recognition, the system manages the order of retrieval, inspection range registration, and size judgment to ensure seamless integration into existing logistics workflows.