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Trajectory control of electro-hydraulic excavator using fuzzy self tuning algorithm with neural network
2009
Journal of Mechanical Science and Technology
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This paper presents the trajectory control of a 2DOF mini electro-hydraulic excavator by using fuzzy self tuning with neural network algorithm. ...
The fuzzy PID and fuzzy self tuning with neural network are designed for circle trajectory following. Its two links are driven by an electric motor controlled pump system. ...
Acknowledgment This research was financially supported by the Ministry of Commerce, Industry and Energy (MC-OIE) and Korea Industrial Technology Foundation (KOTEF) through the Human Resource Training Project ...
doi:10.1007/s12206-008-0817-7
fatcat:br56slklirdczlwv3s6zjnzhxe
Review on Modeling and Control of Flexible Link Manipulators
2020
Modeling, Identification and Control
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A survey of the reported studies is carried out based on the method used for modeling link flexibility and obtaining equations of motion of the FLMs. ...
This paper presents a review of dynamic modeling techniques and various control schemes to control flexible link manipulators (FLMs) that were studied in recent literature. ...
Njeri et al. (2019) presented a self-tuning strain feedback gain controller for high-speed vibration control of a 3D two-link flexible manipulator using the artificial neural network and highlighted that ...
doi:10.4173/mic.2020.3.2
fatcat:jscokhufqjbo7f5gaclkbykgra
A Novel Sample-efficient Deep Reinforcement Learning with Episodic Policy Transfer for PID-Based Control in Cardiac Catheterization Robots
[article]
2021
arXiv
pre-print
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Simulation and experimental trials were done to validate the application of the model, and results obtained shows it could self-tune PID gains appropriately for motion control of a robotic catheter system ...
In this study, a sample-efficient deep reinforcement learning with episodic policy transfer is, for the first time, used for motion control during robotic catheterization with fully adaptive PID tuning ...
[16] applied a PID controller enhanced on neural network for remote motion navigation of a RCS and compared its performance with conventional PID control. ...
arXiv:2110.14941v1
fatcat:incjnx6x3vevxfujn6z2daxwdy
Visual Servoing for Pose Control of Soft Continuum Arm in a Structured Environment
[article]
2022
arXiv
pre-print
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This letter circumvents these challenges by presenting a deep neural network-based method to perform smooth and robust 3D positioning tasks on a soft arm by visual servoing using a camera mounted at the ...
A convolutional neural network is trained to predict the actuations required to achieve the desired pose in a structured environment. ...
DISCUSSION In this paper, we demonstrate that visual servoing using deep neural networks leads to accurate and robust control of a soft continuum arm, which is otherwise known to be hard to control using ...
arXiv:2202.05200v2
fatcat:sk7jptab7vdxhbnaty25osx2lu
Research on grasping model based on visual recognition robot arm
2024
Applied and Computational Engineering
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The amount of the use of robots, especially robotic arms, is increasing rapidly. ...
Based on the understanding of the field of the visual recognition robot arm and consulting a lot of literature, this paper summarizes the current situation of the existing visual recognition robot arm ...
Method The 6 DOF robotic arm is installed with the eye-in-hand camera matched with a neural network. ...
doi:10.54254/2755-2721/41/20230703
fatcat:oedn5efqmbatzh36j3qtjt7mnu
A hybrid neural control scheme for visual-motor coordination
1999
IEEE Control Systems
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The system comprises a pair of charge-couple device (CCD) cameras, each consisting of an array of light sensors and the robot manipulator. ...
The aim is to position the end effector of the The authors are with the ...
Model-Free Approach Using Kohonen's Self-organizing Network The schematic of the system is shown in Fig. 1 . ...
doi:10.1109/37.777787
fatcat:intjptfvjrbnvoah7afcsfwbxm
Editorial: Neural Computation in Embodied Closed-Loop Systems for the Generation of Complex Behavior: From Biology to Technology
2018
Frontiers in Neurorobotics
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This is done by using a detailed dynamical model of a Mass-Spring-Damper (MSD) network. ...
Der and Martius report self-organized behavior of an anthropomorphic musculoskeletal robot arm. ...
doi:10.3389/fnbot.2018.00053
pmid:30214405
pmcid:PMC6125336
fatcat:wl75gxccardnloy63wlngnbl6e
A Review of End-Effector Research Based on Compliance Control
2022
Machines
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control of robot end-effectors have a very broad application prospect. ...
This paper describes the design and research results of different end-effectors under impedance-based control, hybrid force/position control, and intelligent flexible control methods, respectively. ...
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/machines10020100
fatcat:d4rle63enfehfisxglyjly46eq
Self-Organizing Neural Population Coding for improving robotic visuomotor coordination
2011
The 2011 International Joint Conference on Neural Networks
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We present an extension of Kohonen's Self Organizing Map (SOM) algorithm called the Self Organizing Neural Population Coding (SONPC) algorithm. ...
The algorithm adapts online the neural population encoding of sensory and motor coordinates of a robot according to the underlying data distribution. ...
While the arm is moving in front of the camera, a computer uses the camera image to determine the position of the LED, and controls the pan-tilt unit so that the LED is always located at the center of ...
doi:10.1109/ijcnn.2011.6033393
dblp:conf/ijcnn/ZhouDS11
fatcat:77cu5xs4r5ay7ptslwyzogk33e
A Survey on Learning-Based Robotic Grasping
2020
Current Robotics Reports
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Purpose of Review This review provides a comprehensive overview of machine learning approaches for vision-based robotic grasping and manipulation. ...
In contrast, model-based methods allow a precise placement and aim for an automatic configuration without any human intervention to enable a fast and easy deployment. ...
The release velocity is estimated using a physicsbased controller and adjusted based on the residual estimate of the neural network. ...
doi:10.1007/s43154-020-00021-6
fatcat:wsqxh7b6o5cvbf3i4fa2b66eqy
Implementation of self-organizing neural networks for visuo-motor control of an industrial robot
1993
IEEE Transactions on Neural Networks
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We report on the implementation of two neural network algorithms for visuo-motor control of an industrial robot (Puma 562). ...
The first algorithm uses a vector quantization technique, the "neural-gas" network, together with an error correction scheme based on a Widrow-Hoff-type learning rule. ...
Martinetz, who paved the way for the present implementation by carrying out valuable computer simulations and providing code for the "neural gas" algorithm. Thanks also to H. ...
doi:10.1109/72.182698
pmid:18267706
fatcat:wywird6r4zae3lf6zihmmw52oe
The combination of brain-computer interfaces and artificial intelligence: applications and challenges
2020
Annals of Translational Medicine
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Over the past decade, a wide range of BCI applications with AI assistance have emerged. ...
Artificial intelligence (AI), which can advance the analysis and decoding of neural activity, has turbocharged the field of BCIs. ...
Acknowledgments Funding: This study was funded by the National Key R&D Program of China (2018YFC0116500) and the National Natural Science Foundation of China (81770967, 81822010). ...
doi:10.21037/atm.2019.11.109
pmid:32617332
pmcid:PMC7327323
fatcat:vnq3lzgp2fdyndsiv3bx7grooe
Pretrained AI Models: Performativity, Mobility, and Change
[article]
2019
arXiv
pre-print
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We then discuss how pretrained models move through actor networks as a kind of computationally immutable mobile, but that users also act as agents of technological change by reinterpreting them via fine-tuning ...
We further discuss how users may use pretrained models in malicious ways, drawing a novel connection between the responsible innovation and user-centered innovation literatures. ...
Before proceeding, let us briefly describe the technological approach used for transferring a neural network model developed for one task to work on a second task by fine-tuning. ...
arXiv:1909.03290v1
fatcat:7doni7tc3rginpokkow2wtiqmy
A neural-network-based controller for a single-link flexible manipulator using the inverse dynamics approach
2001
IEEE transactions on industrial electronics (1982. Print)
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This thesis presents an intelligent strategy for controlling the tip position of a flexible-link manipulator. ...
The weights of the networks are adjusted using a modified on-line error backpropagation algorithm that is based on the propagation of the redefined output error, derivative of this error and the tip deflection ...
This error will be used subsequently for the weights tuning algorithm of the neural networks. ...
doi:10.1109/41.969386
fatcat:75kgnwvo6bhgzbblhnlmmappna
Design and Evaluation of a Learning-Based Vascular Interventional Surgery Robot
2022
Fibers
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This study utilized a fuzzy-PID controller for precise tool navigation and a neural network model for resistance force modulation with 50 mN precision. ...
However, the absence of apt position control and force feedback remains a challenge. ...
Fuzzy PID is a control algorithm that combines fuzzy logic for self-tuning of the control gains in a PID-based control system. ...
doi:10.3390/fib10120106
fatcat:2tz35lvqdbcwviisgyggxpmjmm
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