Papers
1
Total Citations
2
H-Index
1
About
Dr. Hiroya Makino is a pioneering researcher in robotics and autonomous systems, with a focus on bridging the gap between simulation and real-world deployment for industrial automation. His most notable contribution is the development of a "Visual-Based Forklift Learning System Enabling Zero-Shot Sim2Real Without Real-World Data," a breakthrough that eliminates the need for costly and risky real-world data collection by training autonomous counterbalance forklifts entirely in simulation. This work, published in 2025 and already garnering 2 citations, addresses a critical gap in logistics automation, where versatile counterbalance forklifts are widely used but lack safe, scalable self-driving solutions. By leveraging visual learning and sim-to-real transfer, Makino’s system enables forklifts to operate in diverse industrial settings without prior real-world exposure, significantly reducing deployment barriers. His research stands at the intersection of computer vision, reinforcement learning, and robotics, offering a safer, more efficient path toward automating material handling. Makino’s work is particularly impactful for students and researchers interested in zero-shot transfer learning, as it demonstrates how synthetic environments can unlock practical, real-world autonomy without compromising safety or performance.
Research Focus
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Top Papers
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