Professor Hyun Myung’s Team Wins First Place at Prestigious International Robotics Conference Challenge
24
<(From left) Daebeom Kim (Ph.D. candidate, team leader), Seungjae Lee (Ph.D. candidate), Seoyeon Jang (Ph.D. candidate), Jei Kong (M.S. candidate), Professor Hyun Myung>
The Urban Robotics Lab, led by Professor Hyun Myung from the School of Electrical Engineering, secured the first place overall at the “Nothing Stands Still (NSS) Challenge 2025,”held in the “Future of Construction: Safe, Reliable, and Precise Robots in Construction Environments” workshop at the 2025 IEEE International Conference on Robotics and Automation (ICRA), the world’s premier robotics conference, which took place in Atlanta, USA, from May 19 to 23, 2025.
NSS Challenge is co-hosted by HILTI, a global construction company based in Liechtenstein, and Gradient Spaces Group at Stanford University. It is an advanced version of HILTI SLAM (Simultaneous Localization and Mapping) Challenge, which has been held since 2021, and is now considered one of the most prestigious challenges at ICRA.
<A scene from the oral presentation on the winning team’s technology (presenters: Seungjae Lee and Seoyeon Jang, Ph.D. candidates)>
This challenge evaluates how accurately and robustly LiDAR scan data, collected across various time periods in structurally dynamic environments such as construction and industrial sites, can be registered. Rather than focusing solely on single-instance registration accuracy, it emphasizes multi-session localization and mapping (Multi-session SLAM) technologies capable of handling structural changes over time, making it one of the most technically demanding competitions in the field.
Urban Robotics Lab team secured the first place overall by a significant margin over National Taiwan University (3rd place) and Northwestern Polytechnical University of China (2nd place), with their novel localization and mapping technology that solves the alignment problem of LiDAR data collected across diverse periods and locations. The winning team will be awarded a prize of $4,000.
<Fig. 1. Example of multiway registration of LiDAR scans from different time periods>
Urban Robotics Lab team developed a multiway registration framework capable of robustly aligning multiple scans without prior connectivity information. This framework consists of three core components: CubicFeat, an algorithm that summarizes local features within each scan and identifies correspondences; Quatro, a global registration algorithm that aligns scans based on those correspondences; and Chamelion, a refinement module based on change detection. This combination of techniques shows stable alignment performance even in highly dynamic industrial environments by focusing on static structural elements.
<Fig. 2. Example of change detection using the Chamelion algorithm>
LiDAR scan registration technology is a core component of SLAM used in various autonomous systems, including self-driving cars, autonomous robots, legged platforms, aerial vehicles, and maritime navigation systems. In particular, the awarded technology has demonstrated exceptional precision in estimating the relative poses between scans in complex environments, proving both its academic significance and practical applicability in industry.
Professor Hyun Myung of the School of Electrical Engineering at KAIST stated, “It is deeply meaningful to have demonstrated our technological capabilities by solving multi-session SLAM challenges in complex and constantly changing industrial environments.” He added, “I am grateful to the students who persevered and never gave up, even when many other teams withdrew due to the difficulty of the competition.”
<Competition leaderboard; lower RMSE (Root Mean Square Error) indicates a higher score. (Unit: meters)>
The Urban Robotics Lab team first participated in the SLAM Challenge in 2022, winning 2nd place in the academic division, and in 2023, they took 1st place overall in the LiDAR division and 1st place in the academic division of the vision track.
