Mobile manipulation of humanoid robots-body and leg control for dual arm manipulation

Author(s):  
K. Inoue ◽  
Y. Nishihama ◽  
T. Arai ◽  
Y. Mae
2018 ◽  
Vol 15 (1) ◽  
pp. 172988141875737 ◽  
Author(s):  
Marija Tomić ◽  
Kosta Jovanović ◽  
Christine Chevallereau ◽  
Veljko Potkonjak ◽  
Aleksandar Rodić

In this article, we explore human motion skills in the dual-arm manipulation tasks that include contact with equipment with the final aim to generate human-like humanoid motion. Human motion is analyzed using the optimization approaches starting with the assumption that human motion is optimal. A combination of commonly used optimization criteria in the joint space with the weight coefficients is considered: minimization of kinetic energy, minimization of joint velocities, minimization of the distance between the current and ergonomic positions, and maximization of manipulability. The contribution of each criterion for seven different dual-arm manipulation tasks to provide the most accurate imitation of the human motion is given via suggested inverse optimization approach calculating values of weight coefficients. The effects on actors’ body characteristics and the characteristics of the environment (involved equipment) on the choice of criterion functions are additionally analyzed. The optimal combination of weight coefficients calculated by the inverse optimization approach is used in our inverse kinematics algorithm to transfer human motion skills to the motion of the humanoid robots. The results show that the optimal combination of weight coefficients is able to generate human-like humanoid motions rather than individual one of the considered criterion functions. The recorded human motion and the motion of the humanoid robot ROMEO, obtained with the strategy used by human and defined by our inverse optimal control approach, for the tasks “opening/closing a drawer” are assessed visually and quantitatively.


2004 ◽  
Vol 01 (01) ◽  
pp. 175-198 ◽  
Author(s):  
ROBERT O. AMBROSE ◽  
CATHERINE G. AMBROSE

The primate order of animals is investigated for clues in the design of humanoid robots. The pursuit is directed with a theory that kinematics, musculature, perception, and cognition can be optimized for specific tasks by varying the proportions of limbs, and in particular, the points of branching in kinematic trees such as the primate skeleton. Called the Bifurcated Chain Hypothesis, the theory is that the branching proportions found in humans may be superior to other animals and primates for the tasks of dexterous manipulation and other human specialties. The primate taxa are defined, contemporary primate evolution hypotheses are critiqued, and variations within the order are noted. The kinematic branching points of the torso, limbs and fingers are studied for differences in proportions across the order, and associated with family and genus capabilities and behaviors. The human configuration of a long waist, long neck, and short arms is graded using a kinematic workspace analysis and a set of design axioms for mobile manipulation robots. It scores well. The re-emergence of the human waist, seen in early prosimians and monkeys for arboreal balance, but lost in the terrestrial pongidae, is postulated as benefiting human dexterity. The human combination of an articulated waist and neck will be shown to enable the use of smaller arms, achieving greater regions of workspace dexterity than the larger limbs of gorillas and other hominoidea.


2015 ◽  
Vol 26 (12) ◽  
pp. 3251-3262 ◽  
Author(s):  
Zhijun Zhang ◽  
Zhijun Li ◽  
Yunong Zhang ◽  
Yamei Luo ◽  
Yuanqing Li

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