Control-Oriented Models for Hyperelastic Soft Robots Through Differential Geometry of Curves

Caasenbrood, Brandon J.; Pogromsky, Alexander Yu.; Nijmeijer, Henk

doi:10.1089/soro.2021.0035

Cited by 18 publications

(22 citation statements)

References 38 publications

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“…A special case of the GVS is the piecewise constant-strain approach (PCS) [45], [79], where the strains in the sections are assumed to be constant, an approach which has been extended to closed-chain geometries in [80]. In [81], a similar approach to PCS is presented. Based on the constant curvature (CC) assumption, it also incorporates hyperelastic and viscoelastic material behaviors.…”

Section: ) Absolute Modal-ritz Reductionmentioning

confidence: 99%

Soft Robots Modeling: A Structured Overview

et al. 2023

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The robotics community has seen an exponential growth in the level of complexity of the theoretical tools presented for the modeling of soft robotics devices. Different solutions have been presented to overcome the difficulties related to the modeling of soft robots, often leveraging on other scientific disciplines, such as continuum mechanics, computational mechanics, and computer graphics. These theoretical and computational foundations are often taken for granted and this leads to an intricate literature that, consequently, has rarely been the subject of a complete review. For the first time, we present here a structured overview of all the approaches proposed so far to model soft robots. The chosen classification, which is based on their theoretical and numerical grounds, allows us to provide a critical analysis about their uses and applicability. This will enable robotics researchers to learn the basics of these modeling techniques and their associated numerical methods, but also to have a critical perspective on their uses.

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Section: ) Absolute Modal-ritz Reductionmentioning

confidence: 99%

Soft Robots Modeling: A Structured Overview

et al. 2023

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“…Discrete and modal kinematics simplifies a continuum system to an equivalent finite-state series of rigid or compliant counterparts. The dynamics of such systems can be produced via derivation of the system Lagrangian (based on the elements' kinetic and potential energy [118,133] ), PVW (based on the elements' virtual displacement [104] ), or a recursive computational scheme [133] (also called inverse Newton-Euler algorithm, inverse dynamic model, or reduced-order integration [99,138] ). A continuous representation of the system Lagrangian can be employed for the case of reduced-order modeling.…”

Section: Lagrangian and Tmt Dynamicsmentioning

confidence: 99%

Continuum Robots: An Overview

Russo

Sadati

Dong

et al. 2023

Advanced Intelligent Systems

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When thinking of robots, the image that immediately springs to mind is either an android, designed to resemble human beings and mimic their behavior, or an industrial manipulator, for example, a large machine of rigid steel working in an assembly line. However, robotic systems of multiple forms have been developed to carry out the most diverse tasks, with designs that evolved from readily available structures, such as vehicles, or inspired by nature. In the last decade, more and more bioinspired designs have been enabled by advances in computer science, materials, and manufacturing. Among them, continuum robots, inspired by snakes, trunks, and tendrils, are characterized by a compliant backbone capable of continuous bending, whose shape (configuration, i.e., position and orientation along the backbone curve) is controlled by applying loads through onboard "intrinsic" actuators (e.g., pneumatics or hydraulics) or transmission elements (e.g., tendons, rods, or compliant tubes) that are pushed/pulled from an extremity of the backbone ("extrinsic actuation"). These robots have flexible bodies with a high length to cross-section diameter ratio and are uniquely suited to tasks that require the deployment of tools or sensors with a long reach into tortuous and narrow paths. [1] Continuum robots were first developed in the 1960s [2] and rose to prominence in the late 1990s, [3] when they were often called elephant trunk, [4] tentacle/tendril, [5] or flexible [6] manipulators. Whereas other robots were characterized by intrinsic actuation and larger sizes, research on continuum robots first focused on miniaturization for medical applications, [7,8] leading to extrinsic actuation to enable leaner designs. Recently, continuum robots have been developed for a wider range of applications, including manufacturing, aerospace, search and rescue, and nuclear. In such scenarios, the infinite degrees of freedom (DoFs) of these slender robots enable inspection and intervention in areas that cannot be accessed by conventional robots (e.g., tunnels [9] and gas turbines [10] ).An exhaustive literature search (see Appendix) outlines a surging interest in continuum robots, with a 19.6% average annual growth in publications between 2012 and 2021 (continuum robot search on Web of Science). Three main topics can be observed in recent literature surveys, listed in Table 1. DesignTendon-driven and concentric tube robots are predominant in surveys, but they are not the only design solutions. [18] This richer literature can be attributed to intense research effort toward medical and other small-scale applications when compared to larger-scale tasks (e.g., manipulation) where intrinsic actuation is advantageous.

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“…body due to gravitational acceleration a g , and F e a vector of viscoelastic forces imposed by the stiffness matrix K ≻ 0 and damping matrix D ≻ 0 . The system of matrices can then be efficiently recovered using a Matrix-Differential solver proposed in [10]. This leads to a fast evaluation of (17) as to allow for realtime simulation using precompiled mex files in Matlab.…”

Section: Finite-dimensional Dynamicsmentioning

confidence: 99%

“…All simulation examples and underlying source code are provided publicly on the SOROTOKI toolkit [7] written in Matlab. Here, the numerical integrations of the system matrices ( 18), ( 19), ( 21) and ( 22) are performed using a so-called Matrix-Differential solver (see [10]). The simulations are performed on a modern machine (Ryzen 7-5800H CPU @3.2GHz).…”

Section: Model and Solver Settingmentioning

confidence: 99%

Energy-Shaping Controllers for Soft Robot Manipulators Through Port-Hamiltonian Cosserat Models

2022

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In this work, we discuss the application of energy-based controller design for under-actuated soft robot manipulators. The continuous dynamics of the soft robot are modeled through the differential geometry of Cosserat beams. Using a finite-dimensional truncation, the system can be written as a reduced port-Hamiltonian model that preserves the passivity condition. Then, a model-based controller is introduced that produces a local minimizer of closed-loop potential energy for the desired end-effector configuration. The stabilizing control utilizes an energy-based approach and exploits the passivity of the soft robotic system. The effectiveness of the energy-based controller is demonstrated through extensive simulations of various soft robotic systems that share a resemblance with biology. All software and numerical studies are provided in an open-access SOROTOKI toolkit written in Matlab.

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Control-Oriented Models for Hyperelastic Soft Robots Through Differential Geometry of Curves

Cited by 18 publications

References 38 publications

Soft Robots Modeling: A Structured Overview

Soft Robots Modeling: A Structured Overview

Continuum Robots: An Overview

Energy-Shaping Controllers for Soft Robot Manipulators Through Port-Hamiltonian Cosserat Models

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