학부·대학원

응용지능로봇연구실

응용지능로봇연구실 WELCOME TO OUR LABORATORY 홈페이지 바로가기

연구실소개

The Applied Intelligence & Robotics(AIR) Lab. invites applications for fully-funded MS, Ph.D. positions (starting August 2020) in the areas of sensor fusion, deep learning, SLAM, and autonomous navigation. The positions are open for motivated candidates with a background in Mechanical Engineering, Robotics, Computer Science or Mechatronics. It is expected that mechanical design, computer science, mobile robotics, machine learning, and optimization, as well as analytical/experimental mechanics, will be key features of the research. Candidates with a broad range of technical skills and a track record in translating conceptual ideas into working prototypes will be strongly considered. Evidence of an ability to work in collaborative teams and good communication skills (oral and written) is essential. In addition, successful candidates will be expected to publish scholarly papers and attend international conferences.

연구분야

  • Mobile robots
  • Simultaneous localization and mapping [SLAM]
  • Deep learning
  • Sensor fusion
  • Extended Kalman filter-based Localization
  • Map building and management
  • Indoor navigation
  • Unmanned surface vehicle [USV]
  • Underwater terrain mapping
  • Underwater object detection and tracking
  • 3D point cloud description

보유장비

  • Multibeam sonar – Blueview M900
  • Mobile robot – Scout, Pioneer-3DX, Turtlebot
  • Lidar – VLP-16, SOS Lab-SL1
  • Workstation – GTX 1080 4장

발표논문

· Huu-Thu Nguyen, Eon-Ho Lee, and Sejin Lee, "Study on the Classification Performance of Underwater Sonar Image Classification Based on Convolutional Neural Networks for Detecting a Submerged Human Body," Sensors MDPI, Vol. 20(1), No. 94, Dec 2019.
· Eon-Ho Lee, Yeoungjun Lee, Jinwoo Choi, and Sejin Lee, "Study of Marker Detection Performance on Deep Learning via Distortion and Rotation Augmentation of Training Data on Underwater Sonar Image," Journal of Korea Robotics Society, Vol. 14, No. 1, pp. 14-21, Mar 2019.
· Chul Hee Bae and Sejin Lee, "A Study of 3D Point Cloud Classification of Urban Structures Based on Spherical Signature Descriptor Using LiDAR Sensor Data," Transactions of the Korean Society of Mechanical Engineers A, Vol. 43, No. 2, pp. 85-91, Feb 2019.
· Byungjae Park and Sejin Lee, "Robust Range-Only Beacon Mapping in Multipath Environments," ETRI Journal, Vol. 42, No. 1, Sept 2019.
· Sejin Lee, Byungjae Park, and Ayoung Kim, "Deep Learning from Shallow Dives: Sonar Image Generation and Training for Underwater Object Detection,"  arXiv:1810.07990, Oct. 2018.
· Sejin Lee, "Auto-detection of Submerged Body," Journal of the KSME, Vol. 58, No. 4, pp. 52-56, Apr 2018.
· Byungjae Park, Beom-Su Seo, and Sejin Lee, "LiDAR Image Segmentation using Convolutional Neural Network Model with Refinement Modules," Journal of Korea Robotics Society, Vol. 13, No. 1, pp. 8-15, Feb 2018.
· Eon-Ho Lee and Sejin Lee, "Development of Modified Spherical Signature Descriptor Using 3D Point Cloud Data and Application to Convolutional Neural Network for Urban Structure Classification," Journal of the Korean Society of Mechanical Technology, Vol. 20, No. 1, pp. 18-25, Feb 2018.
· Sejin Lee, Kyoungmin Lee, and Jae-Bok Song, "Development of Sonar Morphology-based Posterior Approach Model for Occupancy Grid Mapping," Robotica, Vol. 35,  pp. 73-84, Jan 2017.
· Sejin Lee, "A New Style of Sonar Sensor Array for Extended Kalman Filter based Localization of Mobile Robots," Journal of the Korean Society of Mechanical Technology, Vol. 19, No. 4, pp. 518-524, Aug 2017.
· Donghyun Kim, Yesenia Velasco, Wei Wang, R. Uma, Rasheed Hussain, and Sejin Lee, "A New Comprehensive RSU Installation Strategy for Cost-Efficient VANET Deployment," IEEE Transactions on Vehicular Technology, Vol. 66, No. 5, pp. 4200-4211, May 2017.
· Eon-ho Lee and Sejin Lee, "Development of Underwater Terrain Map Building Method on Polar Coordinates by Using 3D Sonar Point Clouds," International Journal of Applied Engineering Research, Vol. 11, No. 14, pp. 8259-8264, Aug 2016.
· Sejin Lee and Donghyun Kim, "Spherical Signature Description of 3D Point Cloud and Environmental Feature Learning based on Deep Belief Nets for Urban Structure Classification," Journal of Korea Robotics Society, Vol. 11, No. 3, pp. 115-126, Sept 2016.
· Sejin Lee and Nam Hoon Kim, "A Development of Inspection System for Concentricity of Hole-Saw through Image Analysis," Journal of the Korean Society of Mechanical Technology, Vol. 18, No. 3, pp. 432-438, Jun. 2016.
· Woo-Tae Kim, Sun-gyo Seo, and Sejin Lee, "Taguchi method for optimization of design parameters based on the outlet pressure uniformity of the plasma discharge chamber," Journal of the Korean Society of Mechanical Technology, Vol. 18, No. 1, pp. 11-17, Feb 2016.
· Sejin Lee, Donghyun Kim, and Alade O. Tokuta, "Development of Advanced Sonar Sensor Model for Underwater Terrain Mapping based on Occupancy Grids," International Journal of Applied Engineering Research, Vol. 10, No. 17, pp. 38045-38050, Sept 2015.
· Sejin Lee, Nam-Hun Kim, "Extended Kalman Filter based Localization with Sonar Features extracted by Grid Association for Mobile Robots," International Journal of Applied Engineering Research, Vol. 10, No. 7, pp. 17137-17148, May 2015.
· Woo-Tae Kim and Sejin Lee, "Optimization of Design Parameters for Steel Grating Using Taguchi Method Considering Rigidity and Drainage Efficiency," Transactions of the Korean Society of Mechanical Engineers A, Vol. 38, No. 8, pp. 905-910, Aug 2014.
· Sejin Lee and Kyoungmin Lee, "Development of Web-camera Image Processing-based Natural Landmark Extraction Method for Automatic Welding Using 3-axis Stage," Journal of the Korean Society of Mechanical Technology, Vol. 15, No. 6, pp. 853-860, Dec 2013.