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Sensors 2013, 13(10), 13464-13486; doi:10.3390/s131013464
Article

Robust Kalman Filtering Cooperated Elman Neural Network Learning for Vision-Sensing-Based Robotic Manipulation with Global Stability

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Received: 10 August 2013; in revised form: 2 September 2013 / Accepted: 2 September 2013 / Published: 8 October 2013
(This article belongs to the Section Physical Sensors)
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Abstract: In this paper, a global-state-space visual servoing scheme is proposed for uncalibrated model-independent robotic manipulation. The scheme is based on robust Kalman filtering (KF), in conjunction with Elman neural network (ENN) learning techniques. The global map relationship between the vision space and the robotic workspace is learned using an ENN. This learned mapping is shown to be an approximate estimate of the Jacobian in global space. In the testing phase, the desired Jacobian is arrived at using a robust KF to improve the ENN learning result so as to achieve robotic precise convergence of the desired pose. Meanwhile, the ENN weights are updated (re-trained) using a new input-output data pair vector (obtained from the KF cycle) to ensure robot global stability manipulation. Thus, our method, without requiring either camera or model parameters, avoids the corrupted performances caused by camera calibration and modeling errors. To demonstrate the proposed scheme’s performance, various simulation and experimental results have been presented using a six-degree-of-freedom robotic manipulator with eye-in-hand configurations.
Keywords: visual servoing; dynamic Jacobian estimation; Kalman filtering; Elman neural network; global-state-space visual servoing; dynamic Jacobian estimation; Kalman filtering; Elman neural network; global-state-space
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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MDPI and ACS Style

Zhong, X.; Zhong, X.; Peng, X. Robust Kalman Filtering Cooperated Elman Neural Network Learning for Vision-Sensing-Based Robotic Manipulation with Global Stability. Sensors 2013, 13, 13464-13486.

AMA Style

Zhong X, Zhong X, Peng X. Robust Kalman Filtering Cooperated Elman Neural Network Learning for Vision-Sensing-Based Robotic Manipulation with Global Stability. Sensors. 2013; 13(10):13464-13486.

Chicago/Turabian Style

Zhong, Xungao; Zhong, Xunyu; Peng, Xiafu. 2013. "Robust Kalman Filtering Cooperated Elman Neural Network Learning for Vision-Sensing-Based Robotic Manipulation with Global Stability." Sensors 13, no. 10: 13464-13486.


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