Compensating for Material Deformation in Foldable Robots via Deep Learning ― A Case Study
Mohammad Sharifzadeh,Yuhao Jiang,Amir Salimi Lafmejani,Daniel M. Aukes,Mohammad Sharifzadeh,Yuhao Jiang,Amir Salimi Lafmejani,Daniel M. Aukes
Foldable, origami-inspired, and laminate mechanisms are highly susceptible to deformation under external loading, which can lead to position or orientation errors if idealized kinematic models are used. According to dimensional scaling laws, laminate devices can often be treated as rigid bodies at millimeter and smaller scale deformations. However, foldable mechanisms enter the territory of soft r...
