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Real-Time Motion Tracking of Robot Manipulators Using Adaptive Genetic Algorithms

Mahmoud Tarokh, Xiaomang Zhang
2013 Journal of Intelligent and Robotic Systems  
The paper presents a genetic algorithm approach to real-time motion tracking of redundant and non-redundant manipulators.  ...  The joint angle trajectories are found by applying genetic operators to a set of suitably generated configurations so that the end-effector follows a desired workspace trajectory accurately.  ...  One of the main difficulties of neural networks approaches is that of dealing with multiple solutions (configurations) for a desired end-effector position and orientation.  ... 
doi:10.1007/s10846-013-9860-4 fatcat:lwgz7wnsrrgynapjjcy3uuhsvy

A Repeatable Optimization for Kinematic Energy System with Its Mobile Manipulator Application

Ying Kong, Ruiyang Zhang, Yunliang Jiang, Xiaoyun Xia
2019 Complexity  
neural network (TTZNN) with finite-time convergence is proposed for inverse kinematics of mobile manipulators.  ...  For repeatable motion of redundant mobile manipulators, the flexible base platform and the redundant manipulator have to be returned to the desired initial position simultaneously after completing the  ...  Conflicts of Interest The authors declare that there are no conflicts of interest regarding the publication of this paper.  ... 
doi:10.1155/2019/8642027 fatcat:ldgvntlgrrgytp26zibnszd3im

Fuzzy improved adaptive neuro-NMPC for online path tracking and obstacle avoidance of redundant robotic manipulators

Ashkan M.Z. Jasour, Mohammad Farrokhi
2010 International Journal of Automation and Control  
This paper presents a Nonlinear Model Predictive Control (NMPC) for redundant robotic manipulators.  ...  Using NMPC, the end-effector of the robotic manipulator tracks a predefined geometry path in Cartesian space in such a way that no collision with obstacles in the workspace and no singular configurations  ...  The purpose of the path tracking and the obstacle avoidance for robot manipulators is to obtain a control law such that the end-effector tracks a given geometry path in Cartesian space; and at the same  ... 
doi:10.1504/ijaac.2010.030810 fatcat:ckqgrv24rrcy7oaggfxdq64ni4

RNN for Motion-Force Control of Redundant Manipulators with Optimal Joint Torque [chapter]

Xuefeng Zhou, Zhihao Xu, Shuai Li, Hongmin Wu, Taobo Cheng, Xiaojing Lv
2020 AI based Robot Safe Learning and Control  
For example, track-based controls often fail to grind the robot due to the intolerable impact force applied to the end-effector.  ...  Precise position force control is the core and difficulty of robot technology, especially for robots with redundant degrees of freedom.  ...  of Redundant Manipulators … RNN for Motion-Force Control of Redundant Manipulators … RNN for Motion-Force Control of Redundant Manipulators …  ... 
doi:10.1007/978-981-15-5503-9_6 fatcat:pouof2e5hbatdftsyauvbufjum

RNN Based Adaptive Compliance Control for Robots with Model Uncertainties [chapter]

Xuefeng Zhou, Zhihao Xu, Shuai Li, Hongmin Wu, Taobo Cheng, Xiaojing Lv
2020 AI based Robot Safe Learning and Control  
This control scheme generalizes recurrent neural network based kinematic control of manipulators to that of position-force control, which opens a new avenue to shift position-force control of manipulators  ...  Then an adaptive recurrent neural network is designed to solve the QP problem online.  ...  Summary In this chapter, we propose an adaptive admittance control method for redundant robots based on a recursive neural network.  ... 
doi:10.1007/978-981-15-5503-9_3 fatcat:3w35rq6fhzcmhb5jfp4syueodq

Different-Level Simultaneous Minimization Scheme for Fault Tolerance of Redundant Manipulator Aided with Discrete-Time Recurrent Neural Network

Long Jin, Bolin Liao, Mei Liu, Lin Xiao, Dongsheng Guo, Xiaogang Yan
2017 Frontiers in Neurorobotics  
for fault-tolerant motion planning of redundant manipulator in this paper.  ...  Simulative verifications based on a six-link planar redundant robot manipulator substantiate the efficacy and accuracy of the presented acceleration fault-tolerant scheme, the resultant QP and the corresponding  ...  For example, an adaptive control scheme was provided in Tang et al. (2014) for robot manipulator systems with unknown functions and dead-zone input by using adaptive neural networks, of which the parameters  ... 
doi:10.3389/fnbot.2017.00050 pmid:28955217 pmcid:PMC5601992 fatcat:e4dddmbkzvccbbua74q6w6l37a

Dynamic Neural Networks for Motion-Force Control of Redundant Manipulators: An Optimization Perspective

Zhihao Xu, Shuai Li, Xuefeng Zhou, Songbin Zhou, Taobao Cheng
2020 IEEE transactions on industrial electronics (1982. Print)  
For example, trajectory tracking based control usually fails for grinding robots due to intolerable impact forces imposed onto the end-effectors.  ...  Accurate position-force control is a core and challenging problem in robotics, especially for manipulators with redundant DOFs.  ...  In [22] , a fuzzy recurrent wavelet neural network (RNN) based adaptive force/motion control scheme is proposed for a class of mobile manipulator, which combines the advantages of recurrent technique  ... 
doi:10.1109/tie.2020.2970635 fatcat:naesg3o2tjgvnnop7aor5bfrqe

Real Time Control Application of the Robotic Arm Using Neural Network Based Inverse Kinematics Solution

Nurettin Gökhan ADAR
2021 Sakarya University Journal of Science  
In this study, a multilayered feed-forward Artificial Neural Network model was developed to solve the inverse kinematics of the 5 degrees of freedom robotic arm.  ...  Using the Proportional-Integral control algorithm combined with this Artificial Neural Network model, the real-time position control of the robotic arm was accomplished.  ...  In addition, they declare that Sakarya University Journal of Science and its editorial board have no responsibility for any ethical violations that may be encountered, and that this study has not been  ... 
doi:10.16984/saufenbilder.907312 fatcat:bljcyxf7gjf65ov24xofv22mpu

Tipover Stability Enhancement Of Wheeled Mobile Manipulators Using An Adaptive Neuro- Fuzzy Inference Controller System

A. Ghaffari, A. Meghdari, D. Naderi, S. Eslami
2008 Zenodo  
In this paper an algorithm based on the adaptive neuro-fuzzy controller is provided to enhance the tipover stability of mobile manipulators when they are subjected to predefined trajectories for the end-effector  ...  The controller creates proper configurations for the manipulator to prevent the robot from being overturned.  ...  [6] introduced a simple adaptive fuzzy logic based controller for tracking control of wheeled mobile robots.  ... 
doi:10.5281/zenodo.1076185 fatcat:cnenvhnm6ngbdnjcpqbapx5phu

Inverse Kinematic Control of a Delta Robot Using Neural Networks in Real-Time

Akram Gholami, Taymaz Homayouni, Reza Ehsani, Jian-Qiao Sun
2021 Robotics  
This paper presents an inverse kinematic controller using neural networks for trajectory controlling of a delta robot in real-time.  ...  The parameters of the neural networks are updated while the robot follows a path to adaptively compensate for modeling uncertainties and external disturbances of the control system.  ...  In [33] , a model-free dual neural network for controlling the end-effector of a parallel robot for trajectory tracking is established.  ... 
doi:10.3390/robotics10040115 fatcat:ehwsenrq4jggfcilltsd5rstka

Trajectory generation for mobile manipulators using a learning method

Foudil Abdessemed
2007 2007 Mediterranean Conference on Control & Automation  
The motion of the platform and that of the manipulator are coordinated by a pseudo neural network designed from the kinematics model of the system.  ...  A learning paradigm is used to produce the required reference variables for each of the mobile platform and the robot manipulator for an overall coordinate behavior.  ...  It combines the motion of the robot manipulator with that of the mobile platform to execute an end effector tracking trajectory task.  ... 
doi:10.1109/med.2007.4433659 fatcat:5utgb4s2zbgizi6ota55kc274y

An Exponential Varying-Parameter Neural Network for Repetitive Tracking of Mobile Manipulators

Ying Kong, Qingqing Tang, Jingsheng Lei, Ruiyang Zhang
2020 Complexity  
A novel exponential varying-parameter neural network (EVPNN) is presented and investigated to solve the inverse redundancy scheme of the mobile manipulators via quadratic programming (QP).  ...  To suspend the phenomenon of drifting free joints and guarantee high convergent precision of the end effector, the EVPNN model is applied to trajectory planning of mobile manipulators.  ...  Kinematic control of the robot arm via neural networks is a popular trend for different trajectory tracking.  ... 
doi:10.1155/2020/8520835 doaj:0ed7acab475b4e93a3d7f83441a74df1 fatcat:nbj5h3shyzaodckrxjlrzz2iue

A Learning-based Approach for Adaptive Closed-loop Control of a Soft Robotic Arm

Francesco Pique, Hari Teja Kalidindi, Arianna Menciassi, Cecilia Laschi, Egidio Falotico
2020 Zenodo  
We propose a recurrent neural network (RNN) approach for adaptive model based closed-loop control of a continuum robot.  ...  The characteristic compliance of soft/continuum robot manipulators entails them with the desirable features of intrinsic safety, low power to actuation ratio and adaptability to the environment.  ...  The research leading to these results has received funding from the European Union's Horizon 2020 Research and Innovation Programme in the framework of PROBOSCIS Project (GA No. 863212).  ... 
doi:10.5281/zenodo.4781426 fatcat:rittd7disvghxesocnhksvu67i

Manipulator Trajectory Tracking with a Neural Network Adaptive Control Method

Wenbin Zha, Hui Zhang, Xiangrong Xu, Jude Hemanth
2021 Mathematical Problems in Engineering  
We proposed a neural network adaptive control method with a time-varying constraint state based on the dynamics model of estimation.  ...  the neural network and combining with the estimated value of the inertia matrix.  ...  . e implementation methods include the adaptive control that achieves better end-effector trajectory tracking characteristics in the robot dynamics [4, 5] , neural network control that has universal approximation  ... 
doi:10.1155/2021/9332324 fatcat:6zwwzoxdoraf7l4tkxazqza7q4

Adaptive Neural Network Tracking Control for Manipulators with Uncertainties

Long Cheng, Zeng-Guang Hou, Min Tan, Hong-Ming Wang
2008 IFAC Proceedings Volumes  
An adaptive neural network controller is proposed to deal with the end-effector tracking problem of manipulators with uncertainties.  ...  Finally, the satisfactory performance of the proposed approach is illustrated by simulation results on a PUMA 560 robot.  ...  ADAPTIVE NEURAL NETWORK CONTROLLER The control objective is to develop a task-space tracking controller for the end-effector of robot manipulators with uncertainties and external disturbances.  ... 
doi:10.3182/20080706-5-kr-1001.00402 fatcat:vxnggjn5czaejkgcqmex4gympq
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