A power series based inverse-kinematics solution of a humanoid robot hand with coupled joints

2016 ◽  
Author(s):  
Li Jiang ◽  
Bingqian Sun ◽  
Shaowei Fan ◽  
Qi Zhang
Keyword(s):  
Power Series ◽  
Inverse Kinematics ◽  
Humanoid Robot ◽  
Robot Hand

A Power Series Based Inverse-Kinematics Solution of Humanoid Robot Finger with Coupled Joints

2018 ◽  
Vol 15 (04) ◽  
pp. 1850016
Author(s):  
Li Jiang ◽  
Bingqian Sun ◽  
Haiwei Gu
Keyword(s):  
Power Series ◽  
Inverse Kinematics ◽  
Humanoid Robot ◽  
Linear Interpolation ◽  
Transcendental Equation ◽  
Small Error ◽  
Robot Hand ◽  
Final Solution ◽  
Joint Angles ◽  
Power Series Expansions

Inverse-kinematics is an emphasis and difficulty in the design and application of the humanoid robot hand with coupled joints because of nonlinearity induced by trigonometric transcendental function. In this paper, a power series based inverse-kinematics algorithm is presented, by which the transcendental equation including trigonometric function can be converted into an algebraic equation. An approximate solution is derived first by means of power series expansions; with 1D linear interpolation for errors compensating, the final solution with small error can then be achieved. For robot with linearly coupled joints, the algorithms based on power series expanded to quadratic and quartic terms are used to calculate the accurate joint angles. For robot with nonlinearly coupled joints, the specific procedures are proposed to select appropriate transmission ratio. Simulation and experimental results demonstrate effectiveness of the proposed inverse kinematics method.

Inverse Kinematic Model of Humanoid Robot Hand

2014 ◽  
Vol 611 ◽  
pp. 75-82 ◽  
Author(s):  
Ivan Virgala ◽  
Alexander Gmiterko ◽  
Michal Kelemen ◽  
Ľubica Miková ◽  
Martin Varga
Keyword(s):  
Inverse Kinematics ◽  
Degrees Of Freedom ◽  
Humanoid Robot ◽  
Kinematic Model ◽  
Theoretical Aspect ◽  
Optimization Method ◽  
Inverse Kinematic ◽  
Human Hand ◽  
Robot Hand ◽  
Damped Least Squares

Our study deals with inverse kinematic model of humanoid robot hand. It is important for modeling to know biomechanics of biological human hand, what is discussed in the second section. Based on theoretical aspect of kinematic configuration of the hand, the hand consisting of 24 degrees of freedom is assumed. Subsequently, there are four numerical methods of inverse kinematics used, namely pseudoinverse method, Jacobian transpose method, damped least squares and optimization method. Each of them is simulated in software Matlab and the results are compared and discussed. In the conclusion the best method from the view of solution time and number of iteration cycles is evaluated.

Haptic Teleoperation of Humanoid Robot Hand Using Three-Dimensional Force Feedback

2009 ◽  
Vol 42 (16) ◽  
pp. 431-436 ◽  
Author(s):  
Mai Mishima ◽  
Haruhisa Kawasaki ◽  
Tetsuya Mouri ◽  
Takahiro Endo
Keyword(s):  
Humanoid Robot ◽  
Force Feedback ◽  
Three Dimensional ◽  
Robot Hand

scholarly journals Brain-like functor control machine for general humanoid biodynamics

2005 ◽  
Vol 2005 (11) ◽  
pp. 1759-1779 ◽  
Author(s):  
Vladimir Ivancevic ◽  
Nicholas Beagley
Keyword(s):  
Feedback Control ◽  
Control Systems ◽  
Inverse Kinematics ◽  
Humanoid Robot ◽  
Granule Cells ◽  
Nonlinear Feedback ◽  
Spinal Level ◽  
Cortical Level ◽  
Self Organized ◽  
Neuro Fuzzy

A novel, brain-like, hierarchical (affine-neuro-fuzzy-topological) control for biomechanically realistic humanoid-robot biodynamics (HB), formulated previously in [15, 16], is proposed in the form of a tensor-invariant, “meta-cybernetic” functor machine. It represents a physiologically inspired, three-level, nonlinear feedback controller of muscular-like joint actuators. On the spinal level, nominal joint-trajectory tracking is formulated as an affine Hamiltonian control system, resembling the spinal (autogenetic-reflex) “motor servo.” On the cerebellar level, a feedback-control map is proposed in the form of self-organized, oscillatory, neurodynamical system, resembling the associative interaction of excitatory granule cells and inhibitory Purkinje cells. On the cortical level, a topological “hyper-joystick” command space is formulated with a fuzzy-logic feedback-control map defined on it, resembling the regulation of locomotor conditioned reflexes. Finally, both the cerebellar and the cortical control systems are extended to provide translational force control for moving6-degree-of-freedom chains of inverse kinematics.

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