Kang Park

About

Dr. Kang Park is a researcher in industrial robotics and smart manufacturing, with a focus on optimizing automation systems for efficiency and safety. His work integrates computational intelligence and 3D modeling to address critical challenges in production environments. Notably, his 2023 study on minimizing path lengths for materials and workers in smart factories, which employs a particle swarm optimization algorithm, has garnered 4 citations, highlighting its relevance to Industry 4.0 logistics. In 2022, he advanced collision avoidance for robotic systems by generating 3D robot paths using voxel and vector field methods, a contribution that also earned 4 citations. Earlier, his 2005 paper on a car-body inspection system using industrial robots laid groundwork for automated quality control, with 3 citations. Dr. Park has also explored human-robot interaction, developing an operability evaluation framework for remotely controlled ground combat vehicles in simulated environments (2018, 2 citations). His work bridges theoretical optimization and practical deployment, offering valuable insights for researchers and engineers aiming to enhance productivity and safety in automated systems.

Research Focus

Key Achievements

Top Papers

1. 1
   Minimization of path lengths for materials and workers in smart factories using particle swarm optimization algorithm

   4 citations · 2023
2. 2
   Generation of a 3D robot path for collision avoidance of a workpiece based on voxel and vector field

   4 citations · 2022
3. 3
   Car-body Inspection System Using Industrial Robots

   3 citations · 2005
4. 4
   Development of an Operability Evaluation Framework for Remotely Controlled Ground Combat Vehicles in a Simulated Environment

   2 citations · 2018

Key Collaborators

Contact & Links