The abilities of massive computation parallelism and self-learning make the neural networks a promising candidate for intelligent robot control. In this investigation, a robot controller consisting of inverse kinematics and inverse dynamics algorithms, has been replaced by two neural networks.
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This paper investigates spiking neural networks (SNN) for novel robotic controllers with the aim of improving accuracy in trajectory tracking.
Jun 3, 2022 · In this article, we use a deep network to approximate the Jacobian matrix of a robot with unknown kinematics. An analytic layer-wise deep learning framework is ...
Dec 29, 2023 · In this video, we're going to see if we can control a robot arm using a neural network! Is the robot going to have a mind of its own or will ...
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Apr 12, 2018 · In this paper, we make a relatively comprehensive review of research progress on controlling these robot manipulators by means of neural networks.
Abstract: Neural network theory is applied to theoretical robot kinematics to learn accuracy transforms. The network is trained on accuracy data that ...
Jan 1, 2021 · 1 Background on Neural Networks. 1. 1.1 NEURAL NETWORK TOPOLOGIES AND RECALL . . . . . . . 2. 1.1.1 Neuron Mathematical Model .
Apr 22, 2020 · This article is concerned with developing an intelligent system for the control of a wheeled robot. An algorithm for training an artificial neural network for ...
A neural network architecture for automatic trajectory formation and coordination of multiple effectors during variable speed arm movements.
This book presents and investigates different methods and schemes for the control of robotic arms whilst exploring the field from all angles. On a more specific ...