Paper Info
Title
Imitation of Human Upper-Body Motions by Humanoid Robots
Abstract
This paper presents a method for offline imitation of human upper-body motions. This approach is based on inverse kinematics with task classification which includes an end-effector tracking, joint limits avoidance and joint trajectories tracking, and the results are validated on the humanoid robot NAO. The whole process includes taking data from human using both markerless and marker-based motion capture systems, scaling down the human data to the robot size, calculating the joint angles, and iterating equations of inverse kinematics. After, the final values of joint angles are calculated, they are operated on the real robot using a publisher in Robot Operating System (ROS). On contrary to the studies in literature, we also focus on imitating human motions by a marker-based motion capture system, so we have additional joint orientation information and more accurate results.
Year
DOI
Venue
2019
10.1109/URAI.2019.8768597
2019 16th International Conference on Ubiquitous Robots (UR)
Keywords
Field
DocType
human upper-body motions,offline imitation,inverse kinematics,end-effector tracking,humanoid robot NAO,Robot Operating System,marker-based motion capture system,joint limit avoidance,joint trajectory tracking,marker-based motion capture systems,joint orientation information,markerless motion capture systems,task classification
Motion capture,Computer vision,Kinematics,Task analysis,Inverse kinematics,Computer science,Robot kinematics,Robot end effector,Artificial intelligence,Robot,Humanoid robot
Conference
ISSN
ISBN
Citations 
2325-033X
978-1-7281-3233-4
0
PageRank 
References 
Authors
0.34
5
3
Name
Order
Citations
PageRank
Emre Cemal Gonen100.34
Yu-Jung Chae201.35
ChangHwan Kim316022.61