Human Assistance Group

Human Assistance Group

Research Theme

・Whole-body coordinated movement using deep reinforcement learning
・Standing assistance based on human behavior prediction
・Dressing assistance using deep predictive learning

Research Overview

The AIREC Human Support Team is conducting research that combines AI technology and robotics, with the goal of creating “robots that are close to people and support daily activities.” Using the humanoid robot Dry-AIREC, we are working to realize interactive behaviors that recognize human movements and conditions in real time and flexibly change posture and behavior accordingly. Our goal is to develop technology that enables robots to autonomously support people in caregiving tasks such as transferring, standing up, helping with putting on socks, and changing positions.
“Teaching-by-learning,” which teaches robots human skills, and deep learning using multimodal data enable more natural and adaptive movements. Our major strengths are our end-to-end AI learning of movement generation and our multifaceted approach in collaboration with multiple research teams. In the future, we aim to realize a society in which robots like Dry-AIREC will be active in a variety of settings, not just in caregiving, such as the home, medical care, and business, and in which “one robot that can do everything” lives alongside people. We welcome anyone interested in true symbiosis between humans and robots.

Outcomes and Presentations (Conference Presentations, Publications, etc.)

International Conference

  • Reem Almheiri, Yushi Wang, Tito Pradhono Tomo, Tamon Miyake, Simon Gormuzov, and Shigeki Sugano, “Integrating a 3-Axis Tactile Sensor Array on AIREC Robot for Human-like Radial Pulse Measuring,” the 2026 IEEE/SICE International Symposium on System Integration (SII), 2026.
  • Tai Inui, Tamon Miyake, Yushi Wang, and Shigeki Sugano, “TriForce Band: Leveraging Triaxial Tactile Sensing for Wrist Force-Myography Gesture Recognition,” Extended Abstract of ACM Symposium on User Interface Software and Technology (UIST), pp. 1-3, 2025.
  • Tamon Miyake, Namiko Saito, Tetsuya Ogata, Yushi Wang, Shigeki Sugano, “Deep Predictive Learning with Proprioceptive and Visual Attention for Humanoid Robot Repositioning Assistance,” 2025 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2025.
  • Misa Matsumura, Tamon Miyake, Woohyeok Choi, Shigeki Sugano, Keiichi Nakagawa, Etsuko Kobayashi, “Automated Repositioning from Supine to Lateral with a Humanoid Robot Based on Body Modeling,” 2025 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2025.
  • Sixia Li, Tamon Miyake, Tetsuya Ogata, Shigeki Sugano, Shogo Okada, “Autonomous dialogue generation based on phase boundary detection within continuous motion for domestic robot,” 2025 IEEE International Conference on Robot and Human Interactive Communication (RO-MAN), 2025.
  • Simon Gormuzov, Yushi Wang, Pin-Chu Yang, Tamon Miyake, Tetsuya Ogata, and Shigeki Sugano, “Developing a Framework for Natural Human Movement Mimicry of Low-Dynamic Motions in Based Humanoids,” 2025 IEEE/SICE International Symposium on System Integration (SII), pp. 942-948, 2025.
  • Tamon Miyake, Tetsuya Ogata, Namiko Saito, Riko Kawata, Takuma Tsukakoshi, Masaki Yoshikawa, Shunsuke Aoki, Takumi Akaishi, Yushi Wang, Shigeki Sugano, “AIREC: Demonstration of AI-Driven Robot for Embrace and Care Working in a Domestic Environment,” 40th Anniversary of the IEEE Conference on Robotics and Automation (ICRA 40), Rotterdam, Netherlands, 23-26 September, 2024.
  • Tamon Miyake, Yushi Wang, Pin-chu Yang, and Shigeki Sugano, “Feasibility Study on Parameter Adjustment for a Humanoid Using LLM Tailoring Physical Care,” The 15th International Conference on Social Robotics (ICSR2023), International Conference on Social Robotics, p. 230-243, 2023.
  • Tamon Miyake, Yushi Wang, Gang Yan, and Shigeki Sugano, “Skeleton recognition-based motion generation and user emotion evaluation with in-home rehabilitation assistive humanoid robot,” 2022 IEEE-RAS 21st International Conference on Humanoid Robots (Humanoids), pp. 616-621, 2022.

Domestic Conference

  • Takumi Akaishi, Tamon Miyake, Yushi Wang, Shigeki Sugano, “Development of a Reaching Method Based on Prediction of the Assisted Person’s Movement for Standing Assistance by a Humanoid Robot,” Robotics and Mechatronics Conference 2025 in Yamagata
  • Takuma Tsukakoshi, Tamon Miyake, Tetsuya Ogata, Yushi Wang, Takumi Akaishi, Shigeki Sugano, “Research on close-fitting clothing support based on human and clothing state estimation,” Robotics and Mechatronics 2025 in Yamagata
  • Tamon Miyake, Namiko Saito, Tetsuya Ogata, Yushi Wang, Shigeki Sugano, “Research on generation of assistive motion for changing body position based on deep predictive learning,” Proceedings of the 42nd Annual Conference of the Robotics Society of Japan (RSJ2024), September 3-6, 2024, Osaka.
  • Takumi Akaishi, Tamon Miyake, Yushi Wang, Shigeki Sugano, “Movement Prediction of the Assisted Person for Standing Assistance,” Proceedings of the 42nd Annual Conference of the Robotics Society of Japan (RSJ2024), September 3-6, 2024, Osaka.
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