2019
DOI: 10.1016/j.engappai.2019.06.023
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An incremental unsupervised learning based trajectory controller for a 4 wheeled skid steer mobile robot

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Cited by 15 publications
(5 citation statements)
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References 19 publications
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“…Higher control accuracy is obtained. 17 However, the control algorithm proposed for the robot in this article has a lower computational complexity than the algorithm. Compared with related works, 19 the control algorithm proposed has more parameters.…”
Section: Discussionmentioning
confidence: 99%
See 1 more Smart Citation
“…Higher control accuracy is obtained. 17 However, the control algorithm proposed for the robot in this article has a lower computational complexity than the algorithm. Compared with related works, 19 the control algorithm proposed has more parameters.…”
Section: Discussionmentioning
confidence: 99%
“…A trajectory controller for a four-wheel skid steering mobile robot is proposed. 17 The proposed control system is based on an enhanced self-organizing incremental neural network (NN). Considering the friction dynamics in robot tracking control system, an NN-based composite learning robot control strategy with friction compensation was proposed.…”
Section: Introductionmentioning
confidence: 99%
“…It is responsible for the control of the robot's motion during the process of the predefined path following. For this purpose, the authors in [47] presented the UL algorithm, which was called the enhanced self-organizing incremental neural network (ESOINN). It was introduced by Furao et al in 2007 [70].…”
Section: Unsupervised Learning For Motion Controlmentioning
confidence: 99%
“…But the algorithm is too complex. Juman et al [4] designed a trajectory controller for four-wheel skid steering mobile robots applied in oil palm plantations to track the desired trajectory, with the advantage that the controller can train the network through measured trajectory data and simulated incremental learning data without using kinematics or dynamics models of mobile robots. To make the robot successfully track the desired reference trajectory, Peng et al [5] proposed a symplectic instantaneous optimal control method based on dynamic control differential algebraic equations and verified the robustness and effectiveness of the method through numerical simulation and virtual experiments.…”
Section: Introductionmentioning
confidence: 99%