Rokhmat Febrianto

Papers

Total Citations

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About

Rokhmat Febrianto is a researcher specializing in robotics, with a particular focus on humanoid robot soccer and computer vision. His primary research areas include visual perception, localization, and autonomous navigation for humanoid platforms. Febrianto’s major contributions center on enhancing the robustness of vision systems for the EROS humanoid robot soccer platform, addressing critical challenges in dynamic, color-reduced environments. Notably, his 2018 work on improving field and ball detectors directly tackled performance decrements caused by the RoboCup’s new rules minimizing color coding, achieving 5 citations and advancing real-time object detection under constrained conditions. His 2021 paper introduced a two-step localization approach for competition settings, further refining spatial awareness in humanoid robots. With a cumulative impact of 7 citations from his most-cited works, Febrianto’s research demonstrates practical solutions to real-world robotics problems, bridging the gap between theoretical algorithms and competitive deployment. His achievements highlight a commitment to enabling more reliable and adaptive perception systems, making him a valuable contributor to the humanoid robotics community.