Soft Gripper Dynamics Using a Line-Segment Model With an Optimization-Based Parameter Identification Method

Soft robotics is an emerging field that focuses on the development and application of soft robots. Due to their highly deformable features, it is difficult to model and control such robots. In this paper, we proposed a simplified model to simulate a fluidic elastomer actuator (FEA). The model consis...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:IEEE robotics and automation letters Ročník 2; číslo 2; s. 624 - 631
Hlavní autoři: Zhongkui Wang, Hirai, Shinichi
Médium: Journal Article
Jazyk:angličtina
Vydáno: IEEE 01.04.2017
Témata:
Calibration and identification
Deformable models
direct dynamics formulation
Grasping
Grippers
grippers and other end-effectors
Mathematical model
Robots
Sensors
soft material robotics
Three-dimensional displays
ISSN:2377-3766, 2377-3766
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí:Soft robotics is an emerging field that focuses on the development and application of soft robots. Due to their highly deformable features, it is difficult to model and control such robots. In this paper, we proposed a simplified model to simulate a fluidic elastomer actuator (FEA). The model consists of a series of line segments connected by viscoelastic joints. Pneumatic inputs were modeled as active torques acting at each joint. The Lagrangian dynamic equations were derived. An optimization-based method was proposed to identify the unknown model parameters. Experiments were conducted using three-dimensional (3D) printed FEAs. Calibration results of a single FEA showed the repeatability of the pressure actuated bending angles, and the proposed dynamic model can precisely reproduce the deformation behavior of the FEA. Grasping experiments showed that the proposed dynamic model can predict the grasping forces, which was validated by a separate experiment of grasping force measurement. The presented methods can be extended to model other soft robots.
ISSN:2377-3766
2377-3766
DOI:10.1109/LRA.2017.2650149