Naoki Hiraoka
Papers
11
Total Citations
90
H-Index
5
About
Naoki Hiraoka is a leading researcher in humanoid robotics, specializing in whole-body locomotion, multi-contact motion, and skill acquisition for complex robotic systems. His major contributions span imitation learning, thermal management, and mechanical design. Notably, his work "HumanMimic" (2024, 31 citations) introduces a Wasserstein adversarial imitation learning system that enables humanoid robots to replicate natural human locomotion and seamless transitions, addressing a key challenge in transferring human motion skills to robots. Hiraoka also developed an online learning method for motor core temperature estimation and control (2020, 15 citations), crucial for sustained robot operation. His innovative "Humanoid-Vehicle Transformer" platform (2022, 12 citations) features a plastic resin structure and distributed sensors for versatile shape-shifting robots. Additional achievements include quasi-static multi-contact motion generation (2020, 11 citations) and a multi-fingered hand with a multi-step locking mechanism (2022, 6 citations) for heavy object manipulation. Hiraoka’s work integrates deep reinforcement learning, online adaptation, and mechanical innovation, with over 85 total citations, demonstrating significant impact on advancing humanoid robot capabilities for real-world applications like disaster response and construction.
Research Focus
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