박가람 나성권 송재복 김창환 2024-01-20T22:33:39Z 2024-01-20T22:33:39Z 2021-09-06 2008-10 1976-5622 https://pubs.kist.re.kr/handle/201004/133091 This paper presents a framework to generate human-like movements of a humanoid in real time using the movement primitive database of a human. The framework consists of two processes: 1) the offline motion imitation learning based on an Evolutionary Algorithm and 2) the online motion generation of a humanoid using the database updated by the motion imitation learning. For the offline process, the initial database contains the kinetic characteristics of a human, since it is full of human's captured motions. The database then develops through the proposed framework of motion learning based on an Evolutionary Algorithm, having the kinetic characteristics of a humanoid in aspect of minimal torque or joint jerk. The humanoid generates human-like movements for a given purpose in real time by linearly interpolating the primitive motions in the developed database. The movement of catching a ball was examined in simulation. Korean 제어·로봇·시스템학회 진화 알고리즘을 사용한 인간형 로봇의 동작 모방 학습 및 실시간 동작 생성 Motion Imitation Learning and Real-time Movement Generation of Humanoid Using Evolutionary Algorithm Article 1 제어.로봇.시스템학회 논문지, v.14, no.10, pp.1038 - 1046 제어.로봇.시스템학회 논문지 14 10 1038 1046 scopus kci ART001281340 humanoid evolutionary algorithm imitation learning human-like movement