Results 231 to 240 of about 8,068 (289)

A Pneumatically Actuated Robotic Assistant for MRI-Guided Stereotactic Neurosurgery. [PDF]

IEEE Trans Med Robot Bionics
Li G, Paralikar A, Yarmolenko P, Nankani A, Loew W, Dumoulin C, Cleary K, Oluigbo C, Monfaredi R.   +8 more
europepmc   +1 more source

A spinal network of proprioceptive reflexes can produce a variety of bipedal gaits. [PDF]

Commun Biol
Bunz EK, Haeufle DFB, Schmitt S, Geijtenbeek T.   +3 more
europepmc   +1 more source

A multi-strategy enhanced secretary bird optimization algorithm for high-precision inverse kinematics in robotic arms. [PDF]

PLoS One
Chen X, Lin N, Zhang F, Zhao X.
europepmc   +1 more source

Proprioceptive limit detectors contribute to sensorimotor control of the Drosophila leg. [PDF]

Nat Commun
Pratt BG, Dallmann CJ, Chou GM, Siwanowicz I, Walling-Bell S, Cook A, Sustar A, Azevedo A, Tuthill JC.   +8 more
europepmc   +1 more source

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The Forward Kinematics Solution of Track Irregularity Simulator

Advanced Materials Research, 2012
By means of the bionic optimization method PSO, the particle swarm displacement tracking model was established by this paper according to the displacement constraint conditions of the track irregularity simulator actuators, which took the difference between the given length of the forward kinematics solution and the inverse kinematics solution as the ...
Xiao Ning Cao, Yu Mei Liu, Zheng Jian Lai, Wen Cui Guo, Chao Sun   +4 more
exaly   +2 more sources

Forward kinematics solution of Stewart platform using neural networks

Neurocomputing, 1997
Abstract The Stewart platform's unique structure presents an interesting problem in its forward kinematics (FK) solution. It involves the solving of a series of simultaneous non-linear equations and, usually, non-unique, multiple sets of solutions are obtained from one set of data.
Choon-seng Yee, Kah Bin Lim 0001
exaly   +2 more sources

Inverse kinematics solution using neural networks from forward kinematics equations

2017 9th International Conference on Knowledge and Smart Technology (KST), 2017
This paper presents the inverse kinematics solution using the neural network for a robotic arm in 3-dimension. This paper creates neural networks to represent x, y and z position of the end-effector in the forward kinematics equations. The structure of the network has 4 layers; input layer, 2 hidden layers, and output layer. The input and output layers
Yuttana Kitjaidure
exaly   +2 more sources