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Inverse Kinematics for Humanoid Robots Using Artificial Neural Networks [chapter]

Javier de Lope, Rafaela González-Careaga, Telmo Zarraonandia, Darío Maravall
2003 Lecture Notes in Computer Science  
For this reason, our proposed method considers the use of artificial neural networks to solve the inverse kinematics of the articulated chain that represents the robot's legs.  ...  Since the robot should always remain stable and never fall, the learning set presented to the artificial neural network can be conveniently filtered to eliminate the undesired robot configurations and  ...  [7] use a Hopfield-type neural network to solve the inverse kinematics of a simplified biped robot.  ... 
doi:10.1007/978-3-540-45210-2_41 fatcat:h2l5c563t5hmlfesaqkqnju4tm

Solving the Inverse Kinematics in Humanoid Robots: A Neural Approach [chapter]

Javier de Lope, Telmo Zarraonandia, Rafaela González-Careaga, Darío Maravall
2003 Lecture Notes in Computer Science  
In this paper a method for solving the inverse kinematics of an humanoid robot based on artificial neural networks is presented.  ...  To get a good set of sample data to train the neural network the direct kinematics of the robot needs to be developed, so to formulate the relationship between the joint variables and the position and  ...  For this purpose, it will be necessary to compute the inverse kinematics of the legged robot. The proposed method for solving the inverse kinematics considers the use of an artificial neural network.  ... 
doi:10.1007/3-540-44869-1_23 fatcat:fuqiwjjl5fekvbetgqu7gbasvm

Bilinear Time Delay Neural Network System for Humanoid Robot Software [chapter]

Fumio Nagashima
2007 Humanoid Robots, Human-like Machines  
Fig. 18 show the example of growing neural network for motion. Fig. 20 shows the feedback neural network for stabilize the upper body of humanoid robot.  ...  I discuss the neural network model that is suitable for that sake of common language for all purpose of humanoid robot software system.  ...  Humanoid Robots, Human-like Machines In this book the variety of humanoid robotic research can be obtained.  ... 
doi:10.5772/4820 fatcat:kpu46l7afngyxbhwx5zsbrorla

Cortex inspired model for inverse kinematics computation for a humanoid robotic finger

R. J. Gentili, Hyuk Oh, J. Molina, J. A. Reggia, J. L. Contreras-Vidal
2012 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society  
Here, we expand this previous work by assessing if this cortical model is able to learn the inverse kinematics for an actual anthropomorphic humanoid finger having its two last joints coupled and controlled  ...  Recently, we developed a cortical model that learns the inverse kinematics of a simulated anthropomorphic finger.  ...  Fig 1 . 1 Fig 1.Cortical model for inverse kinematics learning and control of the humanoid finger.  ... 
doi:10.1109/embc.2012.6346608 pmid:23366569 pmcid:PMC3694134 fatcat:cinmuuksnfhtnat6nsha6n5bem

Advanced Robotic Grasping System Using Deep Learning

Pavol Bezak, Pavol Bozek, Yuri Nikitin
2014 Procedia Engineering  
The control is simulated in the Matlab Simulink/ SimMechanics, Neural Network Toolbox and Computer Vision System Toolbox.  ...  In this paper, an intelligent hand-object contact model is developed for a coupled system assuming that the object properties are known.  ...  CAD Model of Simplified Humanoid Robot Hand After kinematic analysis the 3D model of simplified (three-fingered) humanoid hand can be created. For this task the software Autodesk Inventor was used.  ... 
doi:10.1016/j.proeng.2014.12.092 fatcat:bf6olsjz2vhdpflfeyplcjlxge

Motion Planning for Humanoid Robot Based on Hybrid Evolutionary Algorithm

ZHONG Qiu-bo, PIAO Song-hao, GAO Chao
2010 International Journal of Advanced Robotic Systems  
In this paper, online gait control system is designed for walking-up-stairs movement according to the features of humanoid robot, the hybrid evolutionary approach based on neural network optimized by particle  ...  Additionally, through embedded monocular vision, on-site environmental information is collected as neural network input, so necessary joint trajectory is output for the movement.  ...  Artificial neural networks have powerful ability of approximation to solve the nonlinear mapping problem, which can be used to solve a series of problems: manipulator kinematics, path optimization, robot  ... 
doi:10.5772/9703 fatcat:az62n3ottnhnjj5k3w2jiglzky

Momentum control with hierarchical inverse dynamics on a torque-controlled humanoid

Alexander Herzog, Nicholas Rotella, Sean Mason, Felix Grimminger, Stefan Schaal, Ludovic Righetti
2015 Autonomous Robots  
Our results demonstrate that hierarchical inverse dynamics together with momentum control can be efficiently used for feedback control under real robot conditions.  ...  Hierarchical inverse dynamics based on cascades of quadratic programs have been proposed for the control of legged robots.  ...  • Simulated a population of motor cortex neurons for a target-based reaching task • Implemented a simulated brain-machine interface (BMI) using an artificial neural network trained by reinforcement learning  ... 
doi:10.1007/s10514-015-9476-6 fatcat:sc63j3a3anac5pqi36v3tvxz2y

How Rich Motor Skills Empower Robots at Last: Insights and Progress of the AMARSi Project

Andrea Soltoggio, Jochen J. Steil
2012 Künstliche Intelligenz  
How rich motor skills empower robots at last: Insights and progress of the AMARSi project his item ws sumitted to voughorough niversity9s snstitutionl epository y theGn uthorF Citation: yvyqqsyD eF nd  ...  His research interests comprise learning in cognitive robotics, acquisition of motor behavior, modeling of attention, and non-linear systems including recurrent networks.  ...  Wrede, S., Johannfunke, M., Lemme, A., Nordmann, A., Rüther, S., Weirich, A., Steil, J.J.: Interactive learning of inverse kinematics with nullspace constraints using recurrent neural networks.  ... 
doi:10.1007/s13218-012-0192-5 fatcat:3ee4wrnwtzci3ebsox6varnzru

A New Artificial Neural Network Approach in Solving Inverse Kinematics of Robotic Arm (Denso VP6242)

Ahmed R. J. Almusawi, L. Canan Dülger, Sadettin Kapucu
2016 Computational Intelligence and Neuroscience  
A new artificial neural network approach for inverse kinematics is proposed.  ...  This paper presents a novel inverse kinematics solution for robotic arm based on artificial neural network (ANN) architecture. The motion of robotic arm is controlled by the kinematics of ANN.  ...  The authors would like to thank them for their help and support.  ... 
doi:10.1155/2016/5720163 pmid:27610129 pmcid:PMC5005769 fatcat:xte2w2qq3fbmrp6nm72wlhno2a

Artificial neural networks for spatial perception: Towards visual object localisation in humanoid robots

Jurgen Leitner, Simon Harding, Mikhail Frank, Alexander Forster, Jurgen Schmidhuber
2013 The 2013 International Joint Conference on Neural Networks (IJCNN)  
We are using artificial neural networks (ANN) to estimate the location of objects in the robot's environment.  ...  In this paper, we present our on-going research to allow humanoid robots to learn spatial perception.  ...  We use Artificial Neural Networks (ANN) to provide our humanoids with the ability to estimate the location of objects perceived by the robot's cameras.  ... 
doi:10.1109/ijcnn.2013.6706819 dblp:conf/ijcnn/LeitnerHFFS13 fatcat:ivsoifv6pbflrayhhsjgtuolqe

Brain-controlled robots

Mitsuo Kawato
2008 2008 IEEE International Conference on Robotics and Automation  
In January 2008, Duke University and the Japan Science and Technology Agency "JST... publicized their successful control of a brain-machine interface for a humanoid robot by a monkey brain across the Pacific  ...  from neural firing rates in real time.  ...  led us to apply a humanoid robot as a neuroscience tool (Kawato, 2008) .  ... 
doi:10.1109/robot.2008.4543175 dblp:conf/icra/Kawato08 fatcat:kmoisj4vfbeghlu6ghbhfxejlq

Brain controlled robots

Mitsuo Kawato
2008 HFSP Journal  
In January 2008, Duke University and the Japan Science and Technology Agency "JST... publicized their successful control of a brain-machine interface for a humanoid robot by a monkey brain across the Pacific  ...  from neural firing rates in real time.  ...  led us to apply a humanoid robot as a neuroscience tool (Kawato, 2008) .  ... 
doi:10.2976/1.2931144 pmid:19404467 pmcid:PMC2645562 fatcat:wm33yqzw4beapgfk72sucuxn5q

Special issue on machine learning for robotics

Wei Wei, Jinsong Wu, Chunsheng Zhu
2020 Journal of Ambient Intelligence and Humanized Computing  
The paper entitled "Robot Algorithm Based on Neural Network and Intelligent Predictive Control" provided by Yini Wang proposes a novel intelligent predictive control scheme that uses a neural network intelligent  ...  The paper entitled "Kinematics Model Identification and Motion Control of Robot Based on Fast Learning Neural Network" provided by Xuehong Sun introduces a new learning neural network structure, called  ...  The paper entitled "Inverse Kinematics Solution of Robotics Based on Neural Network Algorithms" provided by Ruihua Gao proposes a robotics inverse solution algorithm based on improved BP (back propagation  ... 
doi:10.1007/s12652-020-02567-x fatcat:bnebxk5sobfyvcnuv6amklm2e4

On the improvement of static force capacity of humanoid robots based on plants behavior

Juliano Pierezan, Roberto Zanetti Freire, Lucas Weihmann, Gilberto Reynoso-Meza, Leandro dos Santos Coelho
2016 The European Symposium on Artificial Neural Networks  
This work presents the use of a recent proposed metaheuristic called Runner-Root Algorithm (RRA) applied on the static force capacity optimization of a humanoid robot.  ...  Humanoid robots need to interact with the environment and are constantly in rigid contact with objects.  ...  Neural Networks, Computational Intelligence and Machine Learning.  ... 
dblp:conf/esann/PierezanFWRC16 fatcat:asl5zvvn3zabhgpwe3q43nwqye

Model-based and model-free approaches for postural control of a compliant humanoid robot using optical flow

Sebastien Gay, Jesse van den Kieboom, Jose Santos-Victor, Auke Jan Ijspeert
2013 2013 13th IEEE-RAS International Conference on Humanoid Robots (Humanoids)  
The model-based approach uses inverse kinematics, while the model-free one relies on a neural network as mapping between sensors and actuators.  ...  However, it is widely underused for robotics postural control.  ...  ACKNOWLEDGMENT This work was funded by the Portuguese Fundation for Science and Technology (FCT) through the IST-EPFL joint initiative, EPFL's Biorobotics Laboratory, and the European Commission grant  ... 
doi:10.1109/humanoids.2013.7029955 fatcat:4urbovnyojagza25wmbmy2mhcu
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