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Intelligent Human Robot (NRP RECT) Phase 1B
| Project ID | NRP RECT 1b |
| Partners | Institute for Infocomm Research (I2R), and A*STAR |
| Focus | Assisted Ability, Assistive Robots, HRI |
| Project PI | Prof ANG Wei Tech Executive Director, Rehabilitation Research Institute of Singapore Associate Professor School of Mechanical & Aerospace Engineering and LKC School of Medicine Nanyang Technological University |
| Project Co-PI | Dr Dino ACCOTO Associate Professor, School of Mechanical & Aerospace Engineering Nanyang Technological University Dr ANG Kai Keng Senior Scientist, Neural & Biomedical Technology Institute for Infocomm Research Asst Prof Lyu CHEN Assistant Professor, School of Mechanical & Aerospace Engineering Nanyang Technological University Dr YAU Wei Yun Adjunct Senior Research Scientist Deputy Director (Technical), Rehabilitation Research Institute of Singapore Department Head, Robotics & Autonomous Systems Department Institute for Infocomm Research Dr ZHANG Hai Hong Senior Scientist Institute for Infocomm Resesarch Agency for Science, Technology and Research, Singapore |
The challenge
Lack of mobility is an increasing concern as we see Singapore moving towards an increasingly ageing population.
There needs to be a way to assist the elderly so that they may age in their homes and not be confined to assisted communal living environments.
The proposed solution
As technology becomes more user friendly, smarter and affordable, development of assistive devices is one of the most promising mobility options available today to prepare for a future ageing society.
This programme focuses on the development of a user-centred intelligent Human Robot Interaction (HRI) ROS Toolbox for assistive robots.
It covers three types of assistive robots:
- Machine-on-Man – eg. Lower Limbs & Upper Limbs, e.g. Exoskeletons, etc
- Man-in-Machine – e.g. Man in robotised wheelchair, vehicle, forklift, etc.
- Man-with-Machine – e.g. Feeding robot, patient transfer robot, etc
and two types of people with varying physically function capability:
- Moderate functioning – e.g. generally healthy elderly with declined strength, flexibility, stamina, vision, reaction time, etc. who could use the support in a working environment to keep them employed for longer
- Low functioning – e.g. frail elderly who need assistance with most activities of daily living.
All the work packages in the programme will adopt the same intelligent HRI framework that embraces an AI-enhanced shared control approach, which includes:
- predicting user intents via multiple sensing modalities
- providing real-time adaptive assistance based on user’s performance
- providing safe physical human-robot collaborative control via variable stiffness mechanisms
Human intention recognition algorithms developed based on different sensor modalities will be shared between each work package.
All the work packages will work closely with the Rehabilitation Research Institute of Singapore (RRIS) to leverage RRIS Ability Data – a movement database of healthy people and rehabilitation patients – as a foundation to develop an intelligent data-driven human machine interface.