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Human-Symbiotic Robotics: Leveraging Large Language Models (LLMs) and Foundational Models

ROBOMECH Journal Special Issue

The rapid evolution of large-scale language models, such as GPT variants, has revolutionized human-AI interactions. These models, trained on vast and diverse datasets, are no longer confined to dialogues but are expanding their horizons into robotic action planning. In the realm of robotics, foundational models, especially large language models (LLMs) and visual-language models (VLMs), are predominantly integrated as modules within robotic systems. However, a burgeoning area of research is focusing on creating holistic models that incorporate robot-specific behaviors, aiming for direct robot control.

As our society grapples with an aging population, there's an increasing demand for home caregivers. Lifestyle support robots emerge as potential solutions to this challenge. The future promises robots that seamlessly integrate into human environments, offering both conversation and operational functionalities. This special issue aspires to spotlight the advancements in robots designed for symbiotic human coexistence and the foundational models, like LLMs, that power them.

We invite contributions from pioneers in the domain, emphasizing dialogue systems, intelligent robotics, and their underlying models. This issue also endeavors to shed light on the prospective challenges and opportunities in this pivotal research sphere.

Suggested Topics:

  • Autonomous Intelligent Robotics
  • Human-Robot Interaction Systems
  • Advancements in Large Language Models
  • Lifestyle Support and Caregiver Robots
  • Robotic Action Planning with LLMs
  • Exploration of Foundational Models in Robotics

Submission Procedure:

Any new submission will be processed with single-blind peer review immediately.

To submit a paper, please go to ROBOMECH Journal's submission.

For submission guideline please check here.

When submitting your paper, please select “Human-Symbiotic Robotics: Leveraging Large Language Models (LLMs) and Foundational Models” under “Thematic Series” to be included in this special call.


Simon Egerton is an Associate Professor at La Trobe University Australia and directs the Technology Innovation Lab and the Rural Digital Health Research Group. He specialises in applying technology, Internet of Things and Robotics to improve health and wellbeing outcomes in rural and regional communities through the co-design of digital health research. A notable recent contribution of his was the “Driving digital transformation of regional aged care through the innovation corridor: An Internet of Medical Things Aged Care Service Model” funded project which extended medical services into the homes of those at risk of hospitalization with chronic disease using IoT Technology and was an Australian first.

Naoyuki Kubota is a Professor at the Department of System Design, Tokyo Metropolitan University. He has received the B.Sc. degree from Osaka Kyoiku University, Kashiwara, Japan, in 1992, the M.Eng. degree from Hokkaido University, Hokkaido, Japan, in 1994, and the D.E. degree from Nagoya University, Nagoya, Japan, in 1997. He joined the Osaka Institute of Technology, Osaka, Japan, in 1997. He joined the Department of Human and Artificial Intelligence Systems, University of Fukui, Fukui, Japan, as an Associate Professor, in 2000. He joined the Department of Mechanical Engineering, Tokyo Metropolitan University, Hachioji, Japan, in 2004. He was an Associate Professor, from 2005 to 2012, and has been a Professor with the Department of System Design, Tokyo Metropolitan University, Tokyo, Japan, since 2012.

Akihiro Yorita is a Contract Assistant at the School of Engineering, Kwansei Gakuin University. He graduated from Saitama University in 2007 and earned his M.Eng. from Tokyo Metropolitan University in 2009. In 2023, he secured his Ph.D. from La Trobe University’s Department of Computer Science & IT and became a Visiting Researcher at Tokyo Metropolitan University. A notable contribution of his is the “Robot Assisted Stress Management Framework” presented at the 2018 IEEE Conference. He is an active member of IEEE, JSME, and JSQC, showcasing a commendable blend of technological expertise and academic dedication.

Wei Hong Chin is an esteemed academician with a strong foundation in robotics and automation. He began his academic journey with a B.E. (Hons.) degree from Multimedia University in Malaysia, specializing in Robotics and Automation, which he completed in 2011. Furthering his commitment to the field, he pursued a Master's in Computer Science, which he received from the University of Malaya, Kuala Lumpur, in 2015. His passion for research and innovation led him to Tokyo, where he accomplished his Ph.D. degree from Tokyo Metropolitan University in 2019. Subsequent to his doctoral achievements, he was appointed as an assistant professor in the Department of Systems Design at the same institution. Wei Hong Chin's research is characterized by his focus on biologically-inspired robot navigation, lifelong machine learning, biologically-inspired robot mapping, and multimodal learning. His dedication and expertise are evident in his substantial contribution to the field, with over 20 refereed journal and conference papers under his name. Beyond his publications, he has actively participated and made notable contributions in conferences, having served as the session chair for renowned events such as ICIRA 2019, WCCI 2020, and IJCNN 2021.

Chu Kiong Loo completed his Bachelor of Mechanical Engineering degree with honours at the University of Malaya in 1996. After completing his bachelor’s degree, he began his career as a system engineer at Semiconductor Engineering Manufacturer Sdn. Bhd. at Penang in 1996.  He then received his Ph.D. degree at the University of Science Malaysia in 2004, specializing in neurorobotics and it’s applications in Connected Healthcare.  He began his academic career as a lecturer at the Faculty of Engineering & Technology, Multimedia University. He was promoted to Senior Lecturer in 2008, and then to an Associate Professor in 2010. He served as the Dean of Faculty of Information Science & Technology, Multimedia University. In 2011, he was appointed as a Full Professor at the Department of Artificial Intelligence, Faculty of Computer Science & Information Technology, University of Malaya. His main research interests are neuroscience-inspired machine intelligence. He has published more than 200 peer-reviewed journal and conference papers on neurorobotics and machine intelligence. Prof. Loo is also the recipient of the JSPS fellowship award from Japan and the Georg Forster Fellowship award from the Humboldt Foundation, Germany. He was a visiting professor at the University of Prefecture Osaka University, Japan and King Mongkut's Institute of Technology Ladkrabang, Thailand.

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