gisbi-kim / cv-gskim

1 page cv

More recent news are found here https://bit.ly/giseopkim

Giseop KIM (김기섭)

Summary

• I am a SLAM researcher/engineer. My research interests are state estimation and 3D perception for autonomous robots.
• My main research topic during the Ph.D. has been focused on robust 3D mapping in complex urban sites using LiDAR sensors.
• I have experience in a full pipeline of SLAM in the real world (e.g., from sensor fusion, calibration, odometry, place retrieval, pose-graph optimization, multi-session localization, to long-term map management).

My Channels

• ✉️ Mail: [email protected]
• 💻 Github: gisbi-kim
• 📺 Youtube: bit.ly/giseopkim-youtube

Education

• Korea Advanced Institute of Science and Technology (KAIST) — Feb 2022 (expected)
  • Ph.D. in Civil and Environmental Engineering (CEE)
  • Dissertation: "LiDAR-based Lifelong Robotic Mapping in Changing Environments"
  • Advisor: Dr. Ayoung Kim and Dr. Youngchul Kim
• Korea Advanced Institute of Science and Technology (KAIST) — Feb 2019
  • M.S. in Civil and Environmental Engineering (CEE)
  • Dissertation: "Isovist-induced Robust LiDAR Localization"
  • Advisor: Dr. Ayoung Kim
• Korea Advanced Institute of Science and Technology (KAIST) — Feb 2017
  • B.S. in Civil and Environmental Engineering (CEE)

Selected Publications

2021

• Giseop Kim and Ayoung Kim. “LT-mapper: A Modular Framework for LiDAR-based Lifelong Mapping.” arXiv abs/2107.07712 (2021), Submitted to 2022 IEEE International Conference on Robotics and Automation (ICRA) and Under Review (2022).
• Giseop Kim, Sunwook Choi, and Ayoung Kim. “Scan Context++: Structural Place Recognition Robust to Rotation and Lateral Variations in Urban Environments.” Submitted to IEEE Transactions on Robotics and Under Review (2021).

2020

• Giseop Kim and Ayoung Kim. “Remove, then Revert: Static Point cloud Map Construction using Multiresolution Range Images.” 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (2020): 10758-10765.
• Giseop Kim, Yeong-Sang Park, Younghun Cho, Jinyong Jeong and Ayoung Kim. “MulRan: Multimodal Range Dataset for Urban Place Recognition.” 2020 IEEE International Conference on Robotics and Automation (ICRA) (2020): 6246-6253.
• Younggun Cho, Giseop Kim and Ayoung Kim. “Unsupervised Geometry-Aware Deep LiDAR Odometry.” 2020 IEEE International Conference on Robotics and Automation (ICRA) (2020): 2145-2152.

2019

• Giseop Kim, Byungjae Park and Ayoung Kim. “1-Day Learning, 1-Year Localization: Long-Term LiDAR Localization Using Scan Context Image.” IEEE Robotics and Automation Letters 4 (2019): 1948-1955 (with ICRA 2019).
• Giseop Kim, Ayoung Kim and Youngchul Kim. “A new 3D space syntax metric based on 3D isovist capture in urban space using remote sensing technology.” Comput. Environ. Urban Syst. 74 (2019): 74-87.

2018

• Giseop Kim and Ayoung Kim. “Scan Context: Egocentric Spatial Descriptor for Place Recognition Within 3D Point Cloud Map.” 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (2018): 4802-4809.

Previous Positions

• Graduate Student Research Assistant — Mar. 2017 - Aug. 2021
  • Intelligent Robotic Autonomy and Perception (IRAP) lab, Dept. of Civil and Environmental Engineering, KAIST, South Korea.

Projects

Note

• All projects had been done at IRAP lab of KAIST as Graduate Student Research Assistant.
• The date of the accumulated Cited📰 and Github⭐ counts is 2021.09.06.

1) Dataset Generatation

• MulRan: Multimodal Range dataset
  • tldr: LiDAR + Radar dataset for place recognition evaluations in complex urban sites.
  • role: 1st-author of the paper who conducted all experiments, a project manager who led data acquisitions and manages the dataset site.
  • key result and achievement: paper (ICRA 2020 📰32) and website (https://sites.google.com/view/mulran-pr/home)

2) Constructing Robust Real-time Range sensor-based SLAM system

• Place recognition for range sensors
  • tldr: A fast, versatile, and robust global localizer for various lidar sensors, named Scan Context.
  • role: 1st-author of the paper who conducted all experiments, the writer of whole codes (C++, Matlab, Python).
  • key result and achievement: papers (IROS 2018 📰81, RA-L 2019 📰45) and codes (irapkaist/scancontext ⭐342)
• Complete LiDAR SLAM systems
  • tldr: Plug-and-play loop detection and robust pose-graph SLAM that integrated Scan Context and existing LiDAR odomerty methods to build globally consistent 3D point cloud maps in urban sites.
  • role: I made place recognition (PR) and pose graph optimization (PGO) codes (C++), except the existing the odometry codes. I supported seamless integration of odometry module and PR+PGO module which supports ROS-based interface.
  • key result and achievement: codes (irapkaist/SC-LeGO-LOAM ⭐427, gisbi-kim/SC-LIO-SAM ⭐215, gisbi-kim/SC-A-LOAM ⭐97, gisbi-kim/FAST_LIO_SLAM ⭐58)
• Complete Radar SLAM systems
  • tldr: Urban radar mapping by combining radar Scan Context + radar odometry
  • role: equal to the above LiDAR SLAM systems
  • key result and achievement: codes (gisbi-kim/navtech-radar-slam ⭐36)

3) 3D Map Management/Update in High/Low Dynamic Environments

• Removert
  • tldr: make static map, remove dynamic points, and parse dynamic objects in the wild.
  • role: 1st-author of the paper who conducted all experiments, the writer of the above C++ codes.
  • key result and achievement: paper (IROS 2020 📰8) and codes (irapkaist/removert ⭐136)
• LT-mapper
  • tldr: A modular framework for LiDAR-based lifelong mapping. The first long-term LiDAR mapping open source project.
  • role: 1st-author of the paper who conducted all experiments, the writer of the above C++ codes.
  • key result and achievement: paper (arXiv 2021) and codes (gisbi-kim/lt-mapper ⭐61)

4) SLAM tutorials for Beginners

• Python tutorial
  • tldr: Python-only hands-on experiences for introduction to SLAM
  • role: The writer of the Python codes.
  • key result and achievement: codes (gisbi-kim/PyICP-SLAM ⭐188, gisbi-kim/modern-slam-tutorial-python ⭐26)
• Youtube videos
  • tldr: The video-based tutorials to play and enjoy above open SLAM systems are available via my 📺Youtube
  • role: The maker of the tutorial videos.
  • key result and achievement: videos (bit.ly/giseopkim-youtube)

Services

• Reviewer
  • Journals: T-RO (21), RA-L (21), IJRR (20)
  • Conferences: ICRA (21, 20), IROS (21, 20, 19), UR (21, 20)
• Teaching Assistant
  • 2020 Spring: CE481 (Sensor-based spatial intelligence, a.k.a SLAM 101), CEE, KAIST
  • 2016 Spring: CE352 (Signal and System for Construction IT), CEE, KAIST

Awards

• 2019: ICRA 2019 RAS Travel Grant
• 2018: Best paper award at ICRA 2018 workshop of LTA (Long-term autonomy and deployment of intelligent robots in the real-world)

Skills

• Tools: I am familiar with using C/C++ and Ubuntu/ROS/Ceres/GTSAM/PCL/OpenCV/Eigen/etc.
• Languages: Korean (native), English (fluent)

---

last modified: 2021.09.06