Max Robotics — Global Service Robot Directory + US Certification

About

Changseok Woo is a robotics researcher specializing in autonomous navigation for mobile robots, with a focus on integrating Simultaneous Localization and Mapping (SLAM) with Deep Reinforcement Learning (DRL). His major contributions include the development of novel frameworks—such as SLAM-DRLnav and iNAV-drlSLAM—that combine the mapping and localization strengths of SLAM with the adaptive path-planning capabilities of DRL. These works address critical limitations in indoor self-driving, particularly the challenge of navigating dynamic obstacles that traditional SLAM methods fail to handle. Woo’s research has practical implications for service robotics, as demonstrated by his study on evaluation methods for indoor guide robots, which aims to standardize safety and performance metrics for commercial deployment. With over 14 citations across his most-cited papers, Woo’s work is gaining recognition for bridging the gap between classical robotics and modern AI-driven approaches. His innovative integration of SLAM and DRL offers a promising pathway toward more robust, real-world autonomous navigation systems, making his research highly relevant for students and engineers advancing indoor robotics.