Soft Gripper Dynamics Using a Line-Segment Model With an Optimization-Based Parameter Identification Method - Zhongkui Wang; Hirai, Shinichi (IEEE robotics and automation letters, 2017)
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.