Towards Automatic Design of Soft Pneumatic Actuators: Inner Structure Design Using CNN Model and Bézier Curve-Based Genetic Algorithm - Archive ouverte du site Alsace Access content directly
Journal Articles IEEE Robotics and Automation Letters Year : 2023

Towards Automatic Design of Soft Pneumatic Actuators: Inner Structure Design Using CNN Model and Bézier Curve-Based Genetic Algorithm

Abstract

In this letter, the development of a method for the design of soft pneumatic actuators is described. The focus is given on the interest of using a deep learning model to explore the design space with a genetic algorithm. In particular, we propose to perform the automatic synthesis of the inner structure of pneumatic actuators using Bézier curves and Gaussian Mixture Points, to have a simple representation of the actuator genotype. This makes it possible to represent a wide variety of structures and to take into account the presence of the actuator pneumatic supply. It is shown a CNN model can interestingly be used in conjunction with FEM. FEM is being used to train initially the CNN model and for the control of accuracy, while the CNN model reduces the computational cost, offering a sufficient accuracy during the synthesis thanks to transfer learning. Through two case studies, the capacity of generating geometrically complex designs such as a double-helix network for a twisting actuator is outlined. Its possible extension and further use are also discussed.
Fichier principal
Vignette du fichier
Mosser et al.pdf (2.45 Mo) Télécharger le fichier
Origin Files produced by the author(s)
licence

Dates and versions

hal-04204220 , version 1 (12-06-2024)

Licence

Identifiers

Cite

Loïc Mosser, Laurent Barbé, Lennart Rubbert, Pierre Renaud. Towards Automatic Design of Soft Pneumatic Actuators: Inner Structure Design Using CNN Model and Bézier Curve-Based Genetic Algorithm. IEEE Robotics and Automation Letters, 2023, 8 (10), pp.6603-6610. ⟨10.1109/LRA.2023.3309135⟩. ⟨hal-04204220⟩
45 View
1 Download

Altmetric

Share

Gmail Mastodon Facebook X LinkedIn More