Imitation of the whole body motion based on the knack on a humanoid robot

Author(s):  
K Terada ◽  
Y Ohmura ◽  
Y Kuniyosi
2009 ◽  
Vol 21 (3) ◽  
pp. 311-316 ◽  
Author(s):  
Kensuke Harada ◽  
◽  
Mitsuharu Morisawa ◽  
Shin-ichiro Nakaoka ◽  
Kenji Kaneko ◽  
...  

For the purpose of realizing the humanoid robot walking on uneven terrain, this paper proposes the kinodynamic gait planning method where both kinematics and dynamics of the system are considered. We can simultaneously plan both the foot-place and the whole-body motion taking the dynamical balance of the robot into consideration. As a dynamic constraint, we consider the differential equation of the robot's CoG. To solve this constraint, we use a walking pattern generator. We randomly sample the configuration space to search for the path connecting the start and the goal configurations. To show the effectiveness of the proposed methods, we show simulation and experimental results where the humanoid robot HRP-2 walks on rocky cliff with hands contacting the environment.


2013 ◽  
Vol 479-480 ◽  
pp. 617-621
Author(s):  
Hsien I Lin ◽  
Zan Sheng Chen

Human-to-Humanoid motion imitation is an intuitive method to teach a humanoid robot how to act by human demonstration. For example, teaching a robot how to stand is simply showing the robot how a human stands. Much of previous work in motion imitation focuses on either upper-body or lower-body motion imitation. In this paper, we propose a novel approach to imitate human whole-body motion by a humanoid robot. The main problem of the proposed work is how to control robot balance and keep the robot motion as similar as taught human motion simultaneously. Thus, we propose a balance criterion to assess how well the root can balance and use the criterion and a genetic algorithm to search a sub-optimal solution, making the root balanced and its motion similar to human motion. We have validated the proposed work on an Aldebaran Robotics NAO robot with 25 degrees of freedom. The experimental results show that the root can imitate human postures and autonomously keep itself balanced.


Author(s):  
Satoki Tsuichihara ◽  
Yuya Hakamata ◽  
Gustavo Alfonso Garcia Ricardez ◽  
Jun Takamatsu ◽  
Tsukasa Ogasawara

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