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MLG2 Pro - Pallet differentiation via “Object Recognition”

The article explains how to use the MLG2 Pro to differentiate between various types of pallets via "object recognition".
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Table of Contents


Checking different types of pallet
  • different sizes
  • different No. of foots
  • different space between the foots

Example for different pallet types



    • How many pallets (objects) can be saved in the MLG?
      up to 4 objects – due to the limitation of internal memory
    • Which beam function is internally used for the object recognition?
      RLC Code
    • What method can be used for a bigger No. of different types (more than 4)
      Reading the RLC Code and saving in PLC, evaluation done by the customer himself


How to teach the pallet via "Object Recognition"

  • place the pallet in-between the MLG
    please note: the detection height of the MLG must be bigger than the length of pallet

  • Select one of the available Q-outputs
    proceed as shown below

SOPAS screen shows Teach-image: 

  • Violet = taught pattern
  • Dark green = adjustable tolerance


For customers who do their own RLC interpretation

That offers most flexibility, but requires some programming work. 
The Process Data must be configured for RLC-output. The RLC-pattern for each pallet type must be deposited into the PLC.

Example for RLC evaluation with MLG10A-1340 (10mm pitch)

  • RLC1 & RLC7 = Pallet has entered when RLC1 & RLC7 > 0
  • RLC2 & RLC4 & RLC6 = width of foot (150mm / 140mm / 140mm)
  • RLC3 & RLC5 = space between foots (380mm / 380mm)
  • RLC8 … RLC16 = keep 0 otherwise there is a plausibility fault





pallet differentiation, object recognition, different types of pallets, RCL interpretation