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Mech-Eye Series

This line of 3D vision products contributes to a wide range of applications, including in the manufacturing and distribution industries, thanks to an extensive selection of models and highly versatile image recognition capability.

  • Features
  • Use cases and target objects
  • Example applications
  • Specifications
  • Mech-DLK

Mech-Eye series features

Mech-Eye industrial-use 3D camera

●Comprises an extensive line of 10 models

●Provides a wide field of vision (135 × 90 mm to 3,500 × 2,800 mm)

●Has undergone more than 10,000 hours of continuous operational testing to ensure safety and reliability

Mech-Vision image processing software

●Features leading-edge deep learning technology

●Can recognize a variety of workpieces without CAD inputs

●Is easy to set up thanks to Denso Wave’s proprietary Mech-Eye GUI

Mech-Viz robot control software

●Visualizes recognition results and the robotic environment in 3D

●Supports simulated and real-time interference avoidance and track planning

●Allows you to quickly set up a robot model simply by choosing the model


 

Advantages

Exceptional durability and cost performance

The Mech-Eye industrial-use camera has been tested continuously for 10,000 hours to ensure exceptional durability. In addition, the product offers excellent cost performance since it can accommodate a broad range of target objects and environments utilizing multiple algorithms.

Advanced image processing

Mech-Eye can accommodate a variety of target objects and environments using user-selected recognition methods. It can also accommodate bulk or aligned workpieces, glossy or contrasting workpieces to which tape has been applied, and other workpieces that defy easy recognition.
In addition, users can build image processing systems to suit various applications by using Mech-Vision to add multiple algorithms.

Easy installation and operation

Users need only select the optimal camera from the extensive line of models and complete a simple installation process.

The dedicated GUI is easy to use. Users can also learn how to control the product at Denso Robotics School.


 

Denso Wave’s proprietary Mech-Eye GUI

●Select from the two recognition methods described below. There’s no need for model CAD data.

(1) Matching:Recognizes objects based on profiles created by imaging models and registering their shapes.
This method is suited to bulk workpieces.

(2) Clustering:Recognizes objects whose area matches that of a designated workpiece.
This method is suited to workpieces with a simple shape.

●Configuration can be accomplished entirely by touch operations, ensuring anyone can use the system intuitively.

*Results can be displayed on a Smart TP (if using the RC9) or on a computer monitor (if using the RC8).


 

System architecture


 

Use cases

·Palletizing
·Sorter loading
·Sorting
·Positioning
·Assembly

 

Target objects

Mech-Eye can generate high-quality point cloud data for various objects (boxes, hemp sacks, metal parts, etc.).
  • Tightly packed boxes with patterns or tape
  • Hemp sacks with patterns
  • Bulk boxes
  • Bulk metal parts

 

Application videos

  • Use of AI assisted 3D Camera for Palletizing Returnable Containers

  • Use of 3D Camera and Gripper for Picking Irregularly Shaped


 

Depalletizing of stacked cardboard boxes

Overview and issues

Overview and issues
・Applications in which cardboard boxes stacked on pallets are depalletized

・Applications in which cardboard boxes of mixed shapes are stacked randomly on pallets require 3D image recognition.


Solution
・Use Mech-Eye to realize stable recognition, even when cardboard boxes are stacked randomly.

・·Accommodate multiple types of boxes with deep learning technology.

・Pick a wide variety of box shapes without registering models.



 

Mech-Eye camera

  UHP-140 NANO Pro XS
Model

 
Optimal working distance [mm] 300 ± 20 300~600 300~600
Near/Far FOV [mm] 135 × 90 @ 280mm~
150 × 100 @ 320mm
220 × 150 @ 0.3m~
440 × 300 @ 0.6m
220 × 160 @ 0.3m~
430 × 320 @ 0.6m
Resolution 2048 × 1536 1280 × 1024 1280 × 1024
Point repeatability Z*¹ 2.6μm @ 0.3m
Region*² : 0.09μm @ 0.3m
0.1mm @ 0.5m 0.1mm @ 0.5m
VDI/VDE accuracy*³ 0.03mm @ 0.3m 0.1mm @ 0.5m 0.1mm @ 0.5m
Typical capture time [s] 0.6~0.9 0.6~1.1 0.7~1.1
Baseline [mm] 80 68 93
Dimensions [mm] 260 × 65 × 142 145 × 51 × 85 160 × 52 × 87
Weight [kg] 1.9 0.7 0.8
Operating temperature [℃] 0~45 0~45 0~45
Communications port Gigabit ethernet Gigabit ethernet Gigabit ethernet
Input 24V DC, 3.75A 24V DC, 1.5A 24V DC, 1.5A
Safety and EMC CE/FCC/VCCI/UKCA/KC/ISED/NRTL CE/FCC/VCCI/UKCA/KC/ISED/NRTL CE/FCC/VCCI
IP rating IP65 IP65 IP65
Spec [mm]

 


 
 
  PRO S Log S Log M
Model

 
Optimal working distance [mm] 500~1000 500~1000 800~2000
Near/Far FOV [mm] 370 × 240 @ 0.5m~
800 × 450 @ 1.0m
360 × 250 @ 0.5m~
710 × 490 @ 1.0m
520 × 390 @ 0.8m~
1410 × 960 @ 2.0m
Resolution 1920 × 1200 1280 × 1024 1280 × 1024
Point repeatability Z*¹ 0.05mm @ 1.0m 0.1mm @ 1.0m 0.3mm @ 2.0m
VDI/VDE accuracy*³ 0.1mm @ 1.0m 0.2mm @ 1.0m 0.3mm @ 2.0m
Typical capture time [s] 0.3~0.6 0.3~0.5 0.3~0.5
Baseline [mm] 180 150 280
Dimensions [mm] 265 × 57 × 100 270 × 72 × 130 387 × 72 × 130
Weight [kg] 1.6 2.2 2.4
Operating temperature [℃] 0~45 0~45 0~45
Communications port Gigabit ethernet Gigabit ethernet Gigabit ethernet
Input 24V DC, 3.75A 24V DC, 3.75A 24V DC, 3.75A
Safety and EMC CE/FCC/VCCI/UKCA/KC CE/FCC/VCCI CE/FCC/VCCI
IP rating IP65 IP65 IP65
Spec [mm]
 
  PRO M Deep*⁴ LSR S*⁴
Model

 
Optimal working distance [mm] 1000~2000 1200~3500 500~1500
Near/Far FOV [mm] 800 × 450 @ 1.0m~
1500 × 890 @ 2.0m
1200 × 1000 @ 1.2m~
3500 × 2800 @ 3.5m
480 × 360 @ 0.5m~
1500 × 1200 @ 1.5m
Resolution 1920 × 1200 2048 × 1536 (Depth)
2000 x 1500 (RGB)
2048 × 1536 (Depth)
4000 x 3000/2000 x 1500 (RGB)
Point repeatability Z*¹ 0.2mm @ 2.0m 1.0mm @ 3.0m 0.2mm @ 1.5m
VDI/VDE accuracy*³ 0.2mm @ 2.0m 3.0mm @ 3.0m 1.0mm @ 1.5m
Typical capture time [s] 0.3~0.6 0.5~0.9 0.5~0.9
Baseline [mm] 270 300 140
Dimensions [mm] 353 × 57 × 100 366 × 77 × 92 228 × 77 × 126
Weight [kg] 1.9 2.4 1.9
Operating temperature [℃] 0~45 -10~45 -10~45
Communications port Gigabit ethernet Gigabit ethernet Gigabit ethernet
Input 24V DC, 3.75A 24V DC, 3.75A 24V DC, 3.75A
Safety and EMC CE/FCC/VCCI/UKCA/KC CE/FCC/VCCI/UKCA/KC/ISED/NRTL CE/FCC/VCCI/UKCA/KC/ISED/NRTL
IP rating IP65 IP65 IP67
Spec [mm]

 
  LSR L*⁴
Model
Optimal working distance [mm] 1200~3000
Near/Far FOV [mm] 1200 × 1000 @ 1.2m~
3000 × 2400 @ 3.0m
Resolution 2048 × 1536 (Depth)
4000 x 3000/2000 x 1500 (RGB)
Point repeatability Z*¹ 0.5mm @ 3.0m
VDI/VDE accuracy*³ 1.0mm @ 3.0m
Typical capture time [s] 0.5~0.9
Baseline [mm] 380
Dimensions [mm] 459 × 77 × 86
Weight [kg] 2.9
Operating temperature [℃] -10~45
Communications port Gigabit ethernet
Input 24V DC, 3.75A
Safety and EMC CE/FCC/VCCI/UKCA/KC/ISED/NRTL
IP rating IP65
Spec [mm]
*¹ The standard deviation of the single point Z value for 100 measurements. The measurement target is a ceramic plate.
*² The standard deviation of the difference of the average Z value in two local regions for 100 measurements.
The measurement target is a ceramic plate.
*³ Standard: VDI/VDE2634 Part II.
*⁴ DEEP/LSR S/LSR L:Class 2 laser device.
 

IPC

  Beckhoff IPC C6650 Dedicated IPC for Mech-Eye
OS Windows 10 (64bit)
CPU Intel® CoreTM i7, 3.6GHz, 4cores Intel® CoreTM i5, 4.4GHz, 6cores
Memory 32GB 16GB
HDD 1TB 256GB
Power supply 100-240V AC, 600W AC adapter:AC100-240V~60/50Hz, 2.5A
Camera:DC 24V 7.5A, 180W
Graphics card NVIDIA Quadro P2200  

Mech-DLK deep learning software features

·Mech-DLK is an optional software package that lets customers create deep-learning data.
·Once purchased, it can be used to create multiple learning datasets without additional fees.
·Data security is assured since data doesn’t need to be transferred to any external site.

*DLK: Deep learning kit

 

Example Mech-DLK uses


 

Mech-DLK architecture


 

Recommended operating environment

  Mech-DLK Standard
Operating system (OS) Windows 10 or later *Linux is not supported.
CPU Intel® Core™ i7 or better
Memory 16 GB or greater
Graphics card GeForce RTX 2070 (8 GB) or better
Graphics card driver Ver. 471.68 or later
Graphics card performance NVIDIA GeForce series card with computational capability of 6.1 or greater
  • Features
  • Use cases and target objects
  • Example applications
  • Specifications
  • Mech-DLK

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