FEM-based soft robotic control framework for intracavitary navigation

Abstract

Bio-inspired robotic structure composed of soft actuation units has attracted increasing research interests in its potential and capacity of complying with unstructured and dynamic environment, as well as providing safe interaction with human; however, this inevitably poses technical challenging to achieve steady, reliable control due to the remarkable non-linearity of its kinematics and dynamics. To resolve this challenge, we propose a novel control framework that can characterize the kinematics of a soft continuum robot through the hyper-elastic Finiteelement modeling (FEM). This enables frequent updates of the Jacobian mapping from the user motion input to the endeffector's point of view. Experimental validation has been conducted to show the feasibility of controlling the soft robot for intracavitary path following. This could be the first success to demonstrate the perspectives of achieving stable, accurate and effective manipulation under large change of robot morphology without having to deduce its analytical model. It is anticipated to draw further extensive attention on resolving the bottleneck against the application of FEM, namely its intensive computation. Index Terms-Finite-element modeling (FEM), Soft Robot Motion Control I. INTRODUCTION Recent advances in soft robotics have attracted much research attention. Inspired by nature [1-3], the robot made of soft materials facilitates many applications demanding for safe manipulation interacting with human, as well as excellent compliance with confined, unstructured and dynamic environment. Minimally invasive surgery could be a typical example [4, 5]. The inherent flexibility theoretically poses infinite degrees of freedom (DoFs). Unlike the conventional robots comprising of rigid linkages between joints, the kinematics and dynamics of soft robot cannot be explicit and well-formulated, but also susceptible to structural error due to its hyper non-linearity. Many research attempts [6-9] were to deduce the analytical model which simulates the robot kinematics behavior. Analytical modeling is a common approach to formulate the kinematics of small and simple structured robots [10]. However, in particular for high DoFs or hyperelastic robot structure, the complexity of the model will increase tremendously with the actuation dimensionality, and it will be very challenging to formulate a precise 1

Effects of chamber shapes on maneuverability and control property of endoscope-support soft actuators

“…Additionally, our study sheds light on the role of friction in actuator performance, emphasizing the need to control the interaction between the actuator and the endoscope. This aspect of our research offers insights into material and design considerations for soft actuators, contributing to the broader field of soft robotics and surgical technology as discussed in the works ( Heung et al, 2020 ; Lee et al, 2017 ). By focusing on these specific design elements, our study adds to the understanding of how soft actuators can be optimized for MIS, thus advancing the development of more effective medical robotic tools.…”

“…For a comprehensive study, finite element analysis (FEA) simulations were employed to incorporate seven distinct pneumatic chamber shapes into the model: circular, semicircular, square, rectangular, fake crescent, long fake crescent, and crescent. FEA is a valuable tool that is widely used in soft actuator research ( Wakimoto et al, 2009 ; Rus and Tolley, 2015 ; Marchese et al, 2015 ; Heung et al, 2020 ; Lee et al, 2017 ; Agarwal et al, 2016 ). Owing to its inherent advantages, including cost-effectiveness, design flexibility, and predictive accuracy ( Connolly et al, 2015 ; Cao et al, 2018 ; Duriez, 2013 ; Marechal et al, 2021 ), FEA provides in-depth insights into the internal structural dynamics of soft actuators during bending.…”

Kinematics of Soft Robots by Geometric Computing

“…A numerical approach can also be used to predict the deformation of soft robots by approximating a continuum body with discretized finite elements. With precise modeling formulation of soft materials, Finite element analysis (FEA) has proved its effectiveness in simulating the behavior of soft robots [10], [11]. However, when dealing with large rotational deformation, the high cost of computation by using enterpriselevel FEA software (e.g.…”

“…Conversely, the tradeoff between computing time and accuracy needs to be made when applying a numerical method on real examples with more than 10k elements. Commercial FEA software like Abaqus and ComSol can generate precise calculations of forward kinematics for soft robots [10], [20]; however, small time-steps are needed when confronted with situations of large deformation. For these softwares, high computation cost and slow simulation speed restrict its usage for further solving the IK problem.…”

Learning-Based Visual-Strain Fusion for Eye-in-Hand Continuum Robot Pose Estimation and Control

“…With real-time learning-based sensing feedback available, the design of the continuum robot controller can also leverage the advantages of data-driven refinement [30], [31], [32]. Our previous work had utilized online-learning locally weighted projection regression and Gaussian process regression (GPR) for orientation control [33] and visual servoing control [34], respectively.…”