Max Robotics — Global Service Robot Directory + US Certification

About

Jung Min Pak is a leading researcher in multi-robot localization and state estimation, with a particular focus on developing robust algorithms for wireless sensor networks. His work addresses critical challenges in mobile robotics, including localization under cyberattacks, missing measurements, and non-line-of-sight conditions. Pak’s major contributions center on finite-memory estimators (FMEs), which offer superior performance compared to traditional infinite-memory filters in harsh environments. His 2023 survey on state estimation algorithms for localization has already garnered 15 citations, establishing a foundational reference in the field. In his 2024 study, Pak proposed a secure event-triggered distributed finite-memory localization algorithm that maintains accuracy even under cyberattacks, also earning 15 citations. His 2022 work on distributed finite memory estimation from relative measurements advanced multi-robot localization in challenging conditions. Pak also developed the distributed Frobenius-norm finite memory interacting multiple model (DFFM-IMM) estimation algorithm, which enhances localization precision in wireless sensor networks. His recent FM-SLAC algorithm simultaneously addresses localization and calibration, correcting for wheel slip and drift. Pak’s hybrid PDA/FIR filtering approach further improves indoor localization reliability. His research is highly cited and continues to shape the future of autonomous multi-robot systems.