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About

Naoki Uchiyama is a robotics researcher whose work spans mobile robot navigation, human-robot interaction, and autonomous systems. His most significant contributions lie in trajectory generation, coverage path planning, and collision avoidance — areas where he has consistently advanced both theoretical foundations and practical implementations. Uchiyama's most-cited work, "Real-time smooth trajectory generation for nonholonomic mobile robots using Bézier curves" (2016, 103 citations), established him as a leading voice in elegant motion planning, demonstrating how mathematical curve-fitting techniques can produce fluid, real-world robot trajectories. This theme extends across multiple publications, including vision-based obstacle avoidance and corridor navigation using Bézier curves, reflecting a coherent research philosophy centered on smooth, computationally efficient motion control. His contributions to coverage path planning, including genetic algorithm and hybrid optimization approaches, address critical challenges in autonomous area exploration. Meanwhile, his work on human-operated mobile robots — developing model-reference and collision avoidance control frameworks — highlights a commitment to safe human-robot collaboration. Notable applied work includes the medical assistance robot Terapio and swarm robotics for rehabilitation services, demonstrating meaningful real-world impact. With over 300 cumulative citations, Uchiyama's research bridges rigorous control theory with socially relevant robotic applications.