Kinematic Modeling of a Soft Pneumatic Actuator Using Cubic Hermite Splines Soft material robotic systems provide increased adaptability and flexibility compared to conventional rigid metal robots. The soft systems benefit from their inherent compliance, which enables them to be used in applications that require safe interaction between humans and robots or manipulation in cluttered environment. Despite advancements in recent years research on soft material robots still needs to make progress in terms of modeling for model based control or path planning. The high nonlinearity of soft material robots makes efficient and accurate modeling difficult. In this work we introduce a kinematic modeling approach based on cubic hermite splines. The method is applied to a soft pneumatic actuator and evaluated against the widely used constant curvature approach. The hermite spline offers the possibility of accurate shape reconstruction from simulated or measured deformation data. Both the shape of a robotxe2x80x99s segment and its orientation can be approximated this way. In this paper a machine learning approach is used to train the kinematic relation between actuating pressure and configuration parameters.

Configuration Modeling of a Soft Robotic Element with Selectable Bending Axes This paper presents an approach for modeling new soft robotic materials which possess the ability to control directional stiffness. These materials are inspired by biological systems where movements are enabled by variable stiffness tissue and contraction of localized muscle groups. Here a lowmeltingpoint (LMP) material lattice embedded in an elastomer serves as a rigid skeleton that may be locally melted to allow bending at selectable joint locations. The forward kinematics of the lattice has been modeled using the product of exponentials method with the incorporation of bending axis selectivity. In this paper, we develop this model to account for torques imposed by tendons, and we model the elastomerxe2x80x99s resistance to bending as a torsional spring at the selected joints. Thus we obtain a twoway relationship between tendon forces and joint anglesaxes. The concept of applying traditional robot modeling strategies to selectively compliant robotic structures could enable precise control of dexterous soft robots that satisfy stringent safety criteria.