Using First Principles for Deep Learning and Model-Based Control of Soft Robots

Using First Principles for Deep Learning and Model-Based Control of Soft Robots

Model-based optimal control of soft robots may enable compliant, underdamped platforms to operate in a repeatable fashion and effectively accomplish tasks that are otherwise impossible for soft robots. Unfortunately, developing accurate analytical dynamic models for soft robots is time-consuming, di...

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Bibliographic Details
Main Authors: Curtis C. Johnson, Tyler Quackenbush, Taylor Sorensen, David Wingate, Marc D. Killpack
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-05-01
Series:Frontiers in Robotics and AI
Subjects:
deep learning
model predictive control
soft robots
error modeling
data-driven modeling
dynamics
Online Access:https://www.frontiersin.org/articles/10.3389/frobt.2021.654398/full

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https://www.frontiersin.org/articles/10.3389/frobt.2021.654398/full

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