Design, manufacturing, and inverse dynamic modeling of soft parallel robots actuated by dielectric elastomer actuators
<|reference_start|>Design, manufacturing, and inverse dynamic modeling of soft parallel robots actuated by dielectric elastomer actuators: Soft parallel robots with their manipulation safety and low commercial cost show a promising future for delicate operations and safe human-robot interactions. However, promoting the use of electroactive polymers (EAPs) is still challenging due to the under-improving quality of the product and the dynamic modelling of the collaborations between multiple actuators. This article presents the design, fabrication, modelling and control of a parallel kinematics Delta robot actuated by dielectric elastomer actuators (DEAs). The trade-off between the actuation force and stroke is retaken by an angular stroke amplification mechanism, and the weight of the robot frame is reduced by utilizing 3D puzzling strip structures. A generic way of constructing a high-stability conductive paint on a silicon-based film has been achieved by laser scanning the DE-film and then sandwiching a conductive particle-based electrode with a paint which is mixed by the particles and photosensitive resin. Compared to the wildly used carbon grease, the fabricated electrode shows a higher consistency in its dynamic behaviour before and after the on-stand test. Finally, to predict the output force and inverse motion of the robot end effector, we constructed the inverse dynamic model by introducing an expanded Bergstrom-Boyce model to the constitutive behavior of the dielectric film. The experimental results show a prediction of robot output force with RSME of 12.4% when the end effector remains stationary, and a well-followed trajectory with less than RSME 2.5%.<|reference_end|>
@article{chang2024design,,
    title={Design, manufacturing, and inverse dynamic modeling of soft parallel
  robots actuated by dielectric elastomer actuators},
    author={Jung-Che Chang, Xi Wang, Dragos Axinte, and Xin Dong},
    journal={arXiv preprint arXiv:2409.20344},
    year={2024},
    archivePrefix={arXiv},
    eprint={2409.20344},
    primaryClass={cs.RO cs.SY eess.SY}
}