Data-Driven Kinematic Model of PneuNets Bending Actuators for Soft Grasping Tasks

Abstract

The paper proposes a novel data-driven approximation kinematic (DAK) model to estimate the shape and opening level of a PneuNets soft gripper in relation to the applied pressure signal. The model offers suitable capabilities for implementing in real-time applications involving soft grasping planning and size recognition of fragile objects with different sizes and shapes. The proposed DAK model estimates the free bending behavior of a PneuNets actuator (soft gripper finger) based on a set of approximation functions derived from experimental data and an equivalent serial mechanism that mimics the shape of the actuator. The model was tested for a commercial PneuNets actuator with decreasing chamber height, produced by SoftGripping Co. (Hamburg, Germany). The model validation is accomplished through a set of experiments, where the shape and elementary displacements were measured using a digital image processing technique. The experimental data and the estimated data from the DAK model were compared and analyzed, respectively. The proposed approach has applicability in sensorless/self-sensing bending control algorithms of PneuNets actuators and in soft grasping applications where the robotic system must estimate the opening level of the gripper in order to be able to accomplish its task.

Aspects Regarding the Modelling and Design of 3D-printed Bending Soft Pneumatic Actuators

“…That that the shape of the actuator is a circular deformation curve as can be seen in figure 5. The bending angle vs input pressure characteristics can be modelled as a second order polynomial function as stated in [8,9]. The coefficient of the squared pressure term is inversely proportional with the modulus of elasticity of the material.…”

“…In figure 1 is presented for example a commercial soft gripper with two bending SPAs fingers made from silicone that can be used for grasping soft/fragile objects [9]. The bending motion of the fingers in grip mode can be controlled with a pressure signal from 0÷1.2 bar in this case.…”

“…Obtaining accurate analytical models is challenging due to nonlinear material properties and large deformations of the actuator under pressurization [12]. Statistical models try to overcome these problems by capturing material, and geometrical features of the actuator through experimental data sets [9] but requires a real prototype of SPA to measure those data. Numerical models are usually based on Finite Element Modelling (FEM) implemented in software packages like ANSYS® or Abaqus® and requires high computational resources and a detailed CAD model of the actuator [13].…”

NeuroSuitUp: System Architecture and Validation of a Motor Rehabilitation Wearable Robotics and Serious Game Platform

“…Many researchers have been interested in the bending behaviour of PneuNets actuators in recent years, and as a result, numerical, analytical, and empirical (statistical) models have been constructed to emphasize the relationship between bending angle and input pressure [ 47 ]. Soft robotic gloves with PneuNet actuators may enable flexible and adaptive movements, allowing patients undergoing rehabilitation to make bending motions that safely adhere to human finger motion [ 48 ].…”

Low-Hanging Fruit - An Exploration of Procedural Modelling Tools to make Voxel Printing more Accessible

“…Rigid grippers are poorly equipped to deal with fruit variability and softness, while keeping up with demand for short cycle times in harvesting. Instead compliant end-effectors that have shape morphing properties of soft materials make them better equipped to deal with the variation and fragility of fruit, and will absorb impact force when making contact with humans (Kootstra et al, 2021;Rad et al, 2020). So the compliant mechanisms of soft robotics have real potential to address these end-effector challenges.…”