A four-layer neural network with 49 neurons trained on analytical dynamic model data predicts joint torques for 7-DOF exoskeleton trajectory tracking, augmented by a PD controller, achieving comparable performance to traditional controllers with reduced computation in simulations.
In this research robot’s input trajectories, user weight, and height were considered as the input of the developed deep neural network
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.RO 1years
2022 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Development of a Deep Learning-Driven Control Framework for Exoskeleton Robots
A four-layer neural network with 49 neurons trained on analytical dynamic model data predicts joint torques for 7-DOF exoskeleton trajectory tracking, augmented by a PD controller, achieving comparable performance to traditional controllers with reduced computation in simulations.