정보통신대학원 세미나를 소개합니다.
이번 세미나는 온라인(영어강의)으로 진행 되며, 학부생, 대학원생, 교직원 누구나 참여 가능합니다.
*특강에 참여한 전전 학부생들에게는(대학원생 제외) 소중대 마일리지를 적립해드리니, 관심있는 학생들의 많은 참여 바랍니다. (ZOOM 접속 후 닉네임을 학번, 이름으로 변경 필수!)
▶▶세미나5-정보통신대학원 세미나 2022년 1학기
Towards Natural Motion Generator
최성준 교수
고려대학교
(Korea University)
초록
Motion generation in Robotics has been widely studied owing to its various applicabilities. For example, when given an explicit object function (e.g., minimizing the energy consumption or finding the shortest path), optimization-based or randomized planning methods are well established for this purpose. However, when it comes to generating natural motions, a relatively small number of studies have been made due to its hardness in defining the ‘naturalness’ of motion. Throughout this talk, I will cover how AI technologies can be utilized to generate natural motions of both robots (e.g., legged robots and manipulators) and animated characters. Recently, autonomous robots have been gradually permeating our daily lives, where the necessity of generating natural robotic motions has gained more interest accordingly. However, generating an abundant number of motions for human-like robots from scratch may take an excessive amount of time. Hence, we will first look at how motion capture data can be leveraged to generate humanoid motions, often referred to as motion retargeting. I will also present a robust motion retargeting method to handle noisy motion data estimated from RGB videos (e.g., YouTube). Then, a data-driven motion generation method for animated characters will be presented that can not only generate a natural motion but also stylize the motion. Finally, I would like to share our recent results on perceptive manipulation using reinforcement learning, emphasizing shared autonomy.
＊일시 04월 13일 (수), 13시~
＊ZOOM https://handong.zoom.us/j/86244954271
＊회의ID 862 4495 4271
＊문의 4단계 BK21 AI사업단 (260-3150)
