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About

Ali Sadiyoko is a researcher whose work sits at the compelling intersection of robotics, artificial intelligence, and crowd psychology. His primary research areas include mobile robot navigation, swarm robotics, and the simulation of collective human behavior. Sadiyoko’s most significant contribution is his pioneering application of socio-dynamic models—specifically the Social Force Model—to robotic control. His 2019 paper on a Mamdani-based Fuzzy Logic Controller for obstacle avoidance in wheeled mobile robots, which has garnered 9 citations, demonstrates a practical, intelligent approach to autonomous navigation. Expanding this concept, his 2015 work on consensus algorithms for formation control and obstacle avoidance in groups of humanoid robots represents a novel synthesis of pedestrian crowd dynamics and multi-agent coordination. Earlier, his 2012 simulation of psychological variable propagation in crowds (6 citations) provided foundational insights into how individual actions can escalate into dangerous group behaviors. By translating the subtle, intuitive rules of human crowd movement into robust algorithms for robot teams, Sadiyoko has created a unique bridge between social science and engineering, offering elegant solutions for coordinated, collision-free robotic swarms.