Natural Motion Generation for Humanoid Robots

2006 ◽  
Author(s):  
Kensuke Harada ◽  
Kris Hauser ◽  
Tim Bretl ◽  
Jean-claude Latombe
Keyword(s):  
Humanoid Robots ◽  
Motion Generation ◽  
Natural Motion

Supervoxel Plane Segmentation and Multi-Contact Motion Generation for Humanoid Stair Climbing

2017 ◽  
Vol 14 (01) ◽  
pp. 1650022 ◽  
Author(s):  
Tianwei Zhang ◽  
Stéphane Caron ◽  
Yoshihiko Nakamura
Keyword(s):  
Motion Planning ◽  
Humanoid Robot ◽  
Real Life ◽  
Estimation Method ◽  
Humanoid Robots ◽  
Stair Climbing ◽  
Lidar Data ◽  
Motion Generation ◽  
Prior Models ◽  
Motion Generator

Stair climbing is still a challenging task for humanoid robots, especially in unknown environments. In this paper, we address this problem from perception to execution. Our first contribution is a real-time plane-segment estimation method using Lidar data without prior models of the staircase. We then integrate this solution with humanoid motion planning. Our second contribution is a stair-climbing motion generator where estimated plane segments are used to compute footholds and stability polygons. We evaluate our method on various staircases. We also demonstrate the feasibility of the generated trajectories in a real-life experiment with the humanoid robot HRP-4.

HUMANOID ROBOT MOTION GENERATION SCHEME FOR TASKS UTILIZING IMPULSIVE FORCE

2012 ◽  
Vol 09 (02) ◽  
pp. 1250008 ◽  
Author(s):  
TEPPEI TSUJITA ◽  
ATSUSHI KONNO ◽  
SHUNSUKE KOMIZUNAI ◽  
YUKI NOMURA ◽  
TOMOYA MYOJIN ◽  
...  
Keyword(s):  
Humanoid Robot ◽  
Control Method ◽  
Three Dimensional ◽  
Humanoid Robots ◽  
Impulsive Force ◽  
Motion Generation ◽  
Three Dimensional Model ◽  
Large Force ◽  
The Impact ◽  
Impact Motion

In order to exert a large force on an environment, it is effective to apply impulsive force. We describe the motions in which tasks are performed by applying impulsive force as "impact motions." This paper proposes a way to generate impact motions for humanoid robots to exert a large force and the feedback control method for driving a nail robustly. The impact motion is optimized based on a three dimensional model using sequential quadratic programming (SQP). In this research, a nailing task is taken as an example of impact motion. A dominant parameter for driving a nail strongly is revealed and motions which maximize the parameter are generated considering the robot's postural stability. In order to evaluate the proposed scheme, a life-sized humanoid robot drives nails into a plate made of chemical wood. The optimized motion is compared with a motion designed heuristically by a human. Average driving depth is clearly increased by the proposed method.

scholarly journals Lip Motion Generation Method Based on Formants for Tele-presence Humanoid Robots

2013 ◽  
Vol 31 (4) ◽  
pp. 401-408 ◽  
Author(s):  
Carlos T. Ishi ◽  
Chaoran Liu ◽  
Hiroshi Ishiguro ◽  
Norihiro Hagita
Keyword(s):  
Humanoid Robots ◽  
Motion Generation

Pushing and pulling motion generation for humanoid robots using whole-body momentum control based on analytical inverse kinematics

2020 ◽  
Vol 34 (21-22) ◽  
pp. 1442-1454
Author(s):  
Yuya Hakamata ◽  
Satoki Tsuichihara ◽  
Gustavo Alfonso Garcia Ricardez ◽  
Jun Takamatsu ◽  
Tsukasa Ogasawara
Keyword(s):  
Inverse Kinematics ◽  
Humanoid Robots ◽  
Whole Body ◽  
Motion Generation ◽  
Pushing And Pulling

PERCEPTION OF HUMANOID MOVEMENT

2005 ◽  
Vol 02 (03) ◽  
pp. 277-300 ◽  
Author(s):  
FRANK E. POLLICK ◽  
JOSHUA G. HALE ◽  
MARIA TZONEVA-HADJIGEORGIEVA
Keyword(s):  
Computational Efficiency ◽  
Humanoid Robot ◽  
Relative Effectiveness ◽  
Human Movement ◽  
Humanoid Robots ◽  
Motion Artifacts ◽  
Movement Speed ◽  
Space Representation ◽  
Motion Generation ◽  
Psychological Techniques

With the ultimate goal of producing natural-looking movements in humanoid robots and virtual humans, we examined the visual perception of movements generated by different models of movement generation. The models of movement generation included 14 synthetic motion generation algorithms based on theories of human motor production. In addition, we obtained motion from recordings of actual human movement. The resulting movements were applied to both a humanoid robot and a computer graphics virtual human. The computational efficiency of the motion production algorithms is described. In Experiment 1, we examined observers' judgments of the naturalness of a movement. Results showed that, for the humanoid robot, low ratings of naturalness were obtained for rapid movement. In addition, it was found that some movements that appeared to have unremarkable naturalness ratings were anomalous examples of the desired movement. In Experiment 2, we used naturalness ratings to study the influence of movement speed on the humanoid robot. Results indicated that the decrease in naturalness was due to motion artifacts at the ends of the movement. In Experiment 3, we returned to the issue of anomalous movements by obtaining ratings of similarity between pairs of movements, and analyzing these with multi-dimensional scaling to obtain a psychological space representation of the set of movements. Results showed that the presumed anomalous movements were indeed distinctive from the other movements, suggesting that the naturalness judgments did not completely indicate the perception of movement. We discuss these results in the context of what they suggest for the relative effectiveness of the different generation algorithms at producing natural movement, and their relative computational efficiency, as well as in terms of the effectiveness of different psychological techniques for the assessment of humanoid movement.

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