In-Joo Kim
Papers
1
Total Citations
36
H-Index
1
About
In-Joo Kim is a leading researcher in the field of robotics and autonomous navigation, with a primary focus on simultaneous localization and mapping (SLAM) and sensor fusion. His most cited work, "DV-SLAM (Dual-Sensor-Based Vector-Field SLAM) and Observability Analysis" (2014, 36 citations), makes a foundational contribution by rigorously examining the observability of conventional vector-field SLAM through the Fisher information matrix (FIM). Kim identifies a critical ambiguity that arises when a mobile robot integrates sensor measurements while moving with a fixed heading, demonstrating how such conditions can compromise localization accuracy. This theoretical insight has practical implications for designing more robust SLAM systems, particularly for field robots operating in GPS-denied environments. By advancing the understanding of sensor fusion and observability, Kim’s work helps enable more reliable autonomous navigation in complex, real-world settings. His research continues to influence the development of intelligent robotic systems, bridging the gap between theoretical observability analysis and practical deployment.
Research Focus
Key Achievements
Top Papers
- 1DV-SLAM (Dual-Sensor-Based Vector-Field SLAM) and Observability Analysis36 citations · 2014