top of page

Plenary Session

Title: AI Robots and Moon Shot Program

 

Abstract

There are many ways to make research and development of intelligent robotic systems. I have been working on the Multi-scale robotics systems for many years. It consists of many elements how the system can be structured from the individual to the group/society levels in analogy with the biological system.

 

Focusing on the coevolution and self organization capabilities, I will show a new initiative on AI and Robot, one of the Moon Shot Programs started by Japanese Government, since 2020. Based on the Society 5.0, it is a new and challenging program aiming at the AI robotic system in 2050. I will introduce some of the projects in this program for realization of the Society 5.0 by back-casting technologies from the 2050 to the current ones. It is important to have international cooperation with many research institutions.

ToshioFukuda4.jpg

Prof. Toshio Fukuda
Nagoya University,
Waseda University

Khatib (2).jpg

Prof. Oussama Khatib
Stanford University

 

Plenary Session
Title: From Romeo & Juliet to OceanOne  Deep-Sea Robotic Exploration

 

Abstract
OceanOne is a robotic diver with a high degree of autonomy for physical interaction with the environment while connected to a human expert through an intuitive interface.

 

The robot was recently deployed in several archeological expeditions in the Mediterranean with the ability to reach 1000 meters. Distancing humans physically from dangerous and unreachable spaces while connecting their skills, intuition, and experience to the task.

k
k
Takako Hashimoto.jpg

Prof. Takako Hashimoto
Chiba University of Commerce

Plenary Session
Title: Structuring Topics on Large-Scale Twitter for Discovering People's Perceptions
 

Abstract: Twitter is currently one of the most influential microblogging services on which users interact with messages. This talk introduces a clustering method that automatically discovers coarse-grained topics from large scale Twitter data. We evaluate the computational efficacy of the proposed method and demonstrate its systematic improvement in scalability as the data volume increases. The results of applying the proposed method to a large Twitter data set (26 million tweets) on COVID-19 vaccination in Japan are presented. We also collected over 100 million vaccine-related tweets posted by 8 million users and used the Latent Dirichlet Allocation model to perform automated topic modeling of tweet text during vaccination campaigns in Japan, and show that civic engagement on social platforms contributed to reducing anxiety and speeding up vaccination through social learning and support.

Anuradha Ranasinghe .png

Prof. Anuradha Ranasinghe 
Liverpool Hope University

Plenary Session

Title: Haptic Perception in Robotics
 

Abstract: From the day we are born, the hands become a primary tool for haptic object exploration. Overtime, humans develop the accuracy of haptic object recognition, and the complexity of manual manipulation and exploratory strategies increases. Vision appears to guide the development of manual manipulation and helps to bring meaning to the haptic information being retrieved by the hands. This talk focuses on haptic-based perception in robotics applications especially vision-based haptic applications.  When vision is totally, or partially impaired humans rely on haptic-based perceptions. Thus, haptic-based perception in low auditory/visibility conditions is important in areas like search and rescue. Nevertheless, vision would add another dimension in haptic exploration in many robotics explorations. Therefore the plot of this talk would give you an insight as to how haptic perception would be useful in many robotics exploration and manipulation and what sort of dimension would be useful to enhance the perception of the humans. 

Distinguished Plenary Speakers

Dr.-Joel-Cuello.jpg

Prof. Joel L. Cuello

University of Arizona, USA
Raouf_Naguib2.jpg

Prof. Raouf Naguib

BIOCORE, International U.K.
Marcelo.JPG

Prof. Marcelo Ang

National University of Singapore
bottom of page