iAR Lab Research Direction

p1

1. Intelligent automation

Cutting force measurement (funded by KIMM)

 

  • Motivation: Need to measure clamping force and cutting force
  • Challenge: Embedding sensors, Decoupling Force, dynamic compensation 
  • Goal: Develop a smart-vise device
  • Collaborating with Dr. Park
ee

Manufacturing process smart automation (funded by GN Corporation)

  • Motivation: Need to automate a certain manufacturing process
  • Challenge: A specified system mechanism and vision technology are needed
  • Goal: Develop an automated manufacturing process platform
system
metrology

Low-cost and high-accuracy position tracking system (funded by URGC) 

 

  • Motivation: Need a high-accurate and low-cost tracking device 
  • Challenge: signal drift, tilted local coordinates, and low static/dynamic accuracy
  • Goal: Develop a tracking system based on VR tracker

Robotic 3D bioprinting with vision system

  • Challenge: robotic 3D printing system needs to create and automatically update a tool path
  • Novelty: novel bioprinting, vision-based tool path generation
dd

2. Robotic machining

robot

Cable assisted robotic system (Funded by CFI)

  • Challenge : 50 times lower structural stiffness than that of CNC machine tools
  • Novelty: Installing an optimal configuration of cables at the robot/ Controlling the cable to track the robot’s movement
  • Outcome: 5~10 times stiffness improvement , Milling steel using the robot

Static deflection compensation of robotic machining (Funded by KITECH)

  • Challenge: Robot is easily deflected while machining
  • Novelty: Cutting force estimation using nonlinear disturbance observer & compliance error compensation
  • Outcome: 75% reduction of the static deflection
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