Fusion of Embodied AI and Soft Robotics (FEmAI 2026)
Objectives
Embodied AI is based on the idea that adaptive behavior emerges from the coupling of body, controller, and environment, rather than from the controller alone. Soft robots are a natural fit for this view: their compliant morphology and continuous interaction with the environment make body and behavior inseparable. This special issue gathers recent work at the intersection of AI and soft robotics, with a focus on the joint development of learning, modeling, and control toward robust behavior in the physical world.
Scope
Building on this view, the special issue welcomes articles that combine soft embodiments and AI to tackle challenging problems, including but not limited to dexterous manipulation, soft mechanism design, medical intervention, human-robot interaction, assistive systems, foundation models for robots, and long-horizon skill learning. We also welcome contributions addressing recurring challenges such as sim-to-real learning, high-fidelity digital twins and simulators, and physical hardware representations.
Key Topics
- Learning and control for soft robots — policy learning, model-based control, and co-design of body and controller for compliant systems.
- Dexterous manipulation and contact-rich interaction — exploiting soft embodiments for grasping, in-hand manipulation, and whole-body contact.
- Soft robots for medical, assistive, and human-robot interaction settings — safe, compliant systems for intervention, rehabilitation, and shared physical spaces.
- Foundation models and long-horizon skill learning for embodied agents — large pretrained models, skill abstraction, and planning over extended physical tasks.
- Sim-to-real, digital twins, and hardware representations — high-fidelity simulators, differentiable models of soft bodies, and transfer to physical hardware.
Submission Guidelines
https://kse2026.kse-conferences.org/
Session Organizers
Dr. Nhan Huu Nguyen
Japan Advanced Institute of Science and Technology, Japan, nhnhan@jaist.ac.jp
Website: https://fp.jaist.ac.jp/public/Default2.aspx?id=766&l=1
Bio: Dr. Nguyen is affiliated with the Japan Advanced Institute of Science and Technology (JAIST), where he obtained his Ph.D. in Information Science and founded the SoREI (Soft Robotics and Embodied Intelligence) laboratory. His research sits at the intersection of soft robotics and embodied AI, with active work on multimodal soft sensors, soft mechanism design, and learning-based control for compliant systems.
Prof. Van Anh Ho
Japan Advanced Institute of Science and Technology, Japan, van-ho@jaist.ac.jp
Website: https://fp.jaist.ac.jp/public/Default2.aspx?id=669&l=1
Bio: Prof. Ho is affiliated with the Japan Advanced Institute of Science and Technology (JAIST), where he founded and leads the Soft Haptics laboratory. His current research interests are soft robotics, soft haptic interaction, tactile sensing, grasping and manipulation, and bio-inspired robots. He is a member of The Robotics Society of Japan (RSJ), and a Senior Member of the IEEE. He is serving as an Associate Editor for many prestigious international conferences and journals.
Dr. Tuan Tai Nguyen
Japan Advanced Institute of Science and Technology, Japan, tuan-nguyen@jaist.ac.jp
Bio: Dr. Nguyen is affiliated with the Japan Advanced Institute of Science and Technology (JAIST), where he obtained his Ph.D. in Materials Science. He is the recipient of the prestigious Japan Society for the Promotion of Science (JSPS) Research Fellowship for Young Scientists (DC). His research interests are soft robotics, bio-inspired robots, continuum robots, and tactile sensing.