Seungwook Lim

Pohang University of Science and Technology

Papers

Total Citations

H-Index

About

Seungwook Lim has made significant contributions to the field of simultaneous localization and mapping (SLAM), with a particular focus on hierarchical pose-graph-based approaches. His most notable work introduces the Adaptive Sliding Window (ASW), a novel method that dynamically adjusts the optimization window size in hierarchical SLAM by intelligently eliminating stable portions of the graph. This innovation addresses a critical challenge in robotics—balancing computational efficiency with mapping accuracy in large-scale environments. Lim's research has garnered attention within the SLAM community, with his seminal paper accumulating 5 citations as a foundational reference for adaptive optimization techniques. His work on hierarchical pose-graph SLAM represents an important step toward more scalable and real-time mapping solutions for autonomous systems. By proposing a method that adapts to the complexity of the environment rather than relying on fixed computational budgets, Lim has helped pave the way for more efficient long-term robot navigation. His contributions continue to influence researchers working on incremental SLAM optimization, particularly those seeking to reduce computational overhead without sacrificing map quality in large-scale or dynamic environments.