Modeling and analysis of soft robotic fingers using the fin ray effect

Abstract

Soft grasping of random objects in unstructured environments has been a research topic of predilection both in academia and in industry because of its complexity but great practical relevance. However, accurate modeling of soft hands and fingers has proven a difficult challenge to tackle. Focusing on this issue, this article presents a detailed mathematical modeling and performance analysis of parallel grippers equipped with soft fingers taking advantage of the fin ray effect (FRE). The FRE, based on biomimetic principles, is most commonly found in the design of grasping soft fingers, but despite their popularity, finding a convenient model to assess the grasp capabilities of these fingers is challenging. This article aims at solving this issue by providing an analytic tool to better understand and ultimately design this type of soft fingers. First, a kinetostatic model of a general multi-crossbeam finger is established. This model will allow for a fast yet accurate estimation of the contact forces generated when the fingers grasp an arbitrarily shaped object. The obtained mathematical model will be subsequently validated by numerically to ensure the estimations of the overall grasp strength and individual contact forces are indeed accurate. Physical experiments conducted with 3D-printed fingers of the most common architecture of FRE fingers will also be presented and shown to support the proposed model. Finally, the impact of the relative stiffness between different areas of the fingers will be evaluated to provide insight into further refinement and optimization of these fingers.

A 3D-Printed Fin Ray Effect Inspired Soft Robotic Gripper with Force Feedback

“…The fish fin structure allows the robotic gripper to be more adaptive and relatively stable when gripping objects, allowing it to cope with different objects with ease [25]. The characteristics and advantages of the Fin Ray structure have been systematically investigated in previous studies with structural modeling, calculations, and experiments [14,26]. Therefore, we have adopted the Fin Ray structure as well as the inner patterns.…”

“…Here, we used a DS3225 servo motor from DSSERVO with a torque of 25 kg and a servo weight of 60 g. There is an overhead structure between the base of the gripper and the upper plate, which, due to the wire pulling, causes the space between them to change so that the fin- The fish fin structure allows the robotic gripper to be more adaptive and relatively stable when gripping objects, allowing it to cope with different objects with ease [25]. The characteristics and advantages of the Fin Ray structure have been systematically investigated in previous studies with structural modeling, calculations, and experiments [14,26]. Therefore, we have adopted the Fin Ray structure as well as the inner patterns.…”

“…In contrast to the two-fingered configuration, the three-fingered configuration will put the object in a more balanced position and will have a larger contact surface area when holding an object. Therefore, we chose to use three fingers in our gripper design, which are equally distributed with the structure of the robotic fingers inspired by fish fins [12][13][14][15]. Taking use of the Fin Ray effect, the gripper can automatically wrap around the grasped object regardless of its shape.…”

A Deep Learning Method for Vision Based Force Prediction of a Soft Fin Ray Gripper Using Simulation Data

“…Work has been performed to produce a kinetostatic model of the FRE grippers for force estimation (Shan and Birglen, 2020 ). This approach constructs a pseudo rigid body mechanics model, with parameters taken from the geometry and a finite element model.…”

Force analysis of minimal self-adaptive fingers using variations of four-bar linkages

“…Amongst these soft grippers, many can be found built using a particular design of bio-inspired fingers based on the Fin Ray Effect (FRE; see Fig. 1) (Crooks et al, 2017;Shan and Birglen, 2020) for which commercial products exist and are marketed by the company Festo. Underactuation and soft grasping are two common techniques to provide robotic systems with tools for securing and manipulating arbitrarily shaped objects.…”