The team of Professor Daisuke Chugo, School of Engineering, received the Local Organising Committee Award, Environmental Robotics Application for Sustainability, 1st Prize, at the awards ceremony of the 25th International Conference on Climbing and Walking Robots and the Support Technologies (CLAWAR2022) held on September 13, 2022, in Ponta Delgada, Portugal. This prize, newly established this year, is awarded for technology that contributes to the sustainability of society and for technological presentations that contribute to the post-COVID era.
CLAWAR2022 is the 25th meeting of the International Conference Series on Climbing and Walking Robots and the Support Technologies for Mobile Machines, and original submissions were solicited in the general area of mobile robotics, covering climbing, walking, flying robots with assistance and service provided to humans and machines. The conference covered analysis (modelling and simulation) techniques, design approaches, and practical applications and realizations of robotic systems, and the paper by Prof. Chugo and his co-authors was selected as the best paper out of 60 papers published in the proceedings of this conference.
The title of Prof. Chugo's winning submission is "Human models simulating the physical conditions of elderly individuals and a standing assistance method based on these models." This paper proposes a method for having a robot estimate the degree of weakness of elderly individuals by measuring how much force they can exert in six or more simple movements, rather than the conventional method of measuring the degree of weakness of their bodies by using various biometric sensors, in order to design standing assistance movements that are perfectly suited to each individual. The method is groundbreaking, in that it allows for estimates of physical fitness without roboticists having to meet directly with elderly people who are at high risk due to the COVID-19 pandemic.
The co-authors of this paper are Yuya Miyazaki (first-year master's student at Kwansei Gakuin University), Associate Professor Satoshi Muramatsu (Tokai University), Professor Sho Yokota (Toyo University), Professor Jin-Hua She (Tokyo University of Technology) and Professor Hiroshi Hashimoto (Advanced Institute of Industrial Technology). This research was funded by an Individual Special Research Subsidy from Kwansei Gakuin University and a Grant-in-Aid for Scientific Research (B) (20H04566).