scholarly journals Multicriteria Optimal Humanoid Robot Motion Generation

10.5772/4865 ◽  
2007 ◽  
Author(s):  
Genci Capi ◽  
Yasuo Nasu ◽  
Mitsuhiro Yamano ◽  
Kazuhisa Mitobe
Keyword(s):  
Humanoid Robot ◽  
Robot Motion ◽  
Motion Generation

Humanoid robot motion generation for nailing task

2008 ◽  
Author(s):  
Teppei Tsujita ◽  
Atsushi Konno ◽  
Shunsuke Komizunai ◽  
Yuki Nomura ◽  
Takuya Owa ◽  
...  
Keyword(s):  
Humanoid Robot ◽  
Robot Motion ◽  
Motion Generation

MOTION GENERATION FOR THE UPPER BODY OF HUMANOID ROBOT

2010 ◽  
Vol 07 (02) ◽  
pp. 281-294 ◽  
Author(s):  
DENGPENG XING ◽  
JIANBO SU
Keyword(s):  
Energy Consumption ◽  
Humanoid Robot ◽  
Upper Body ◽  
Whole Body ◽  
Robot Motion ◽  
Motion Generation ◽  
Motion Stability ◽  
Simulation Results ◽  
Yaw Moment

This paper aims at the guarantee of yaw moment requirement for the ZMP convention. In order to compensate for the yaw moment of whole body during motion, we present two motion generation methods for the upper body of the humanoid robot. The ground reactive torque and the effect of arms swinging on whole body locomotion are analyzed. Therefore trunk spinning and arms swinging methods are planned to improve the robot motion stability, based on compensating for the yaw moment. These two methods are further compared with each other from the viewpoint of energy consumption. The performance and the feasibility of the proposed methods are evaluated by the simulation results.

Adaptive arm motion generation of humanoid robot operating in dynamic environments

2014 ◽  
Vol 41 (2) ◽  
pp. 124-134 ◽  
Author(s):  
Zulkifli Mohamed ◽  
Mitsuki Kitani ◽  
Genci Capi
Keyword(s):  
Humanoid Robot ◽  
Dynamic Environments ◽  
Robot Motion ◽  
Robot Arm ◽  
Objective Functions ◽  
Motion Generation ◽  
Content Type ◽  
Neural Controllers ◽  
Wide Range ◽  
Arm Motion

Purpose – The purpose of this paper is to compare the performance of the robot arm motion generated by neural controllers in simulated and real robot experiments. Design/methodology/approach – The arm motion generation is formulated as an optimization problem. The neural controllers generate the robot arm motion in dynamic environments optimizing three different objective functions; minimum execution time, minimum distance and minimum acceleration. In addition, the robot motion generation in the presence of obstacles is also considered. Findings – The robot is able to adapt its arm motion generation based on the specific task, reaching the goal position in simulated and experimental tests. The same neural controller can be employed to generate the robot motion for a wide range of initial and goal positions. Research limitations/implications – The motion generated yield good results in both simulation and experimental environments. Practical implications – The robot motion is generated based on three different objective functions that are simultaneously optimized. Therefore, the humanoid robot can perform a wide range of tasks in real-life environments, by selecting the appropriate motion. Originality/value – A new method for adaptive arm motion generation of a mobile humanoid robot operating in dynamic human and industrial environments.

scholarly journals Hierarchical quadratic programming: Fast online humanoid-robot motion generation

2014 ◽  
Vol 33 (7) ◽  
pp. 1006-1028 ◽  
Author(s):  
Adrien Escande ◽  
Nicolas Mansard ◽  
Pierre-Brice Wieber
Keyword(s):  
Quadratic Programming ◽  
Humanoid Robot ◽  
Robot Motion ◽  
Motion Generation

Six-and-a-half-month-old children positively attribute goals to human action and to humanoid-robot motion

2005 ◽  
Vol 20 (2) ◽  
pp. 303-320 ◽  
Author(s):  
Kazunori Kamewari ◽  
Masaharu Kato ◽  
Takayuki Kanda ◽  
Hiroshi Ishiguro ◽  
Kazuo Hiraki
Keyword(s):  
Humanoid Robot ◽  
Human Action ◽  
Robot Motion

Jumping Motion Generation for Humanoid Robot Using Arm Swing Effectively and Changing in Foot Contact Status *

2020 ◽  
Author(s):  
H. Mineshita ◽  
T. Otani ◽  
M. Sakaguchi ◽  
Y. Kawakami ◽  
H.O. Lim ◽  
...  
Keyword(s):  
Humanoid Robot ◽  
Motion Generation ◽  
Arm Swing

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.

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