Papers
3
Total Citations
31
H-Index
3
About
Junho Choi is a researcher specializing in autonomous mobile robotics, with a focus on multi-robot systems, visual-inertial odometry, and intelligent surveillance. His work addresses critical challenges in robot localization and coordination, particularly in environments where GPS is unavailable. Choi’s most cited paper, “MIR-VIO: Mutual Information Residual-based Visual Inertial Odometry with UWB Fusion for Robust Localization” (2021, 20 citations), introduces a novel fusion of visual-inertial data with ultra-wideband (UWB) signals to overcome scale ambiguity in monocular visual odometry, significantly enhancing localization accuracy for drones and mobile robots. In “MASS: Multi-Agent Scheduling System for Intelligent Surveillance” (2022, 8 citations), he develops a scheduling framework that integrates localization, obstacle avoidance, and path planning for autonomous security robots, advancing the deployment of multi-robot teams in indoor surveillance. His recent work, “Multi-Robot Cooperative Localization with Single UWB Error Correction” (2024, 3 citations), tackles error correction in relative positioning among robot teams, improving task distribution and collision avoidance. With contributions that bridge sensor fusion and multi-agent coordination, Choi’s research is shaping robust, scalable solutions for real-world robotic applications.
Research Focus
Key Achievements
Top Papers
- 1
- 2MASS: Multi-Agent Scheduling System for Intelligent Surveillance8 citations · 2022
- 3Multi-Robot Cooperative Localization with Single UWB Error Correction3 citations · 2024