Design and control of a novel variable stiffness soft arm

Hao, Lina; Xiang, Chaoqun; Giannaccini, Maria Elena; Cheng, Hongtai; Zhang, Ying; Nefti‐Meziani, Samia; Davis, Steve

doi:10.1080/01691864.2018.1476179

Cited by 25 publications

(17 citation statements)

References 33 publications

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“…10 illustrates the experimental and simulation results. In order to emphasize the effects of structural and material properties of the PAM along with the distributed weights and external loads on the performance estimation of the manipulator, previous research [53] on the constant curvature model is used as control results. In Fig.…”

Section: Experimental Validationmentioning

confidence: 99%

Stiffness Analysis of a Pneumatic Soft Manipulator Based on Bending Shape Prediction

Zhang

Chen

et al. 2020

IEEE Access

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Soft manipulators can perform continuous operations due to their inherent compliance and dexterity, thus enabling safe interactions and smooth movements in confined environments. However, high compliance usually means low load capacity. It is important for a soft manipulator to possess proper flexibility while maintaining an acceptable stiffness to widen its applications. This paper has hence devoted efforts to a kind of variable stiffness mechanism for a soft manipulator actuated by pneumatic artificial muscles (PAMs). Due to the combination of contractile and extensor PAMs, the manipulator is able to vary its stiffness independently from the configuration. The stiffness characteristics of the soft manipulator are quantitatively analyzed by bending shape prediction under different loading and inflation conditions, and the prediction is built upon a nonlinear statics model coupled with PAM nonlinearity and the Cosserat theory. In addition, experimental measurements are conducted to further validate the expected performance of the manipulator design. The experimental and verified theoretical analysis results indicate that the manipulator shape and stiffness are greatly affected by the pressure variation of PAMs, realizing a large bending space with a high output force. The variable stiffness design obviously increases the manipulator's ability to resist additional interference at the same position. INDEX TERMS Soft manipulator, PAM, bending shape prediction, variable stiffness, the Cosserat theory. LINA HAO received the Ph.D. degree in control theory and control engineering from Northeastern University, China, in 2001. From 2005 to 2006, she worked as a Visiting Researcher with Michigan State University, USA. She is currently a Professor with the School of Mechanical Engineering and Automation, Northeastern University. Her main research interests include design and control of micro-nano robotic systems, bionic drivers of artificial muscles, and smart sensors and actuators. She is a Fellow of the IEEE Robotics and Automation Society and the International Society of Bionic Engineering.

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Section: Experimental Validationmentioning

confidence: 99%

Stiffness Analysis of a Pneumatic Soft Manipulator Based on Bending Shape Prediction

Zhang

Chen

et al. 2020

IEEE Access

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“…Thus, Equations (16) and (17) are the joint variables for a desired position and orientation of Σ M . Then, the length of the cables C 1 and C 2 can be obtained using Equations (12) and (13), respectively.…”

Section: Inverse Kinematic Position Analysismentioning

confidence: 99%

“…These new type of robots cannot be studied in the same way as conventional manipulators; new strategies for their analyses are being proposed. For example, Hao et al [12] presented a mechanism composed of four pneumatic muscles, and they obtained its kinematic analysis with geometric parameters. Greer et al [13] presented a mechanism that combines pneumatic muscle, a spring and a wire, the motion of which is similar to that presented in [6], and its kinematic analysis is based on geometric parameters and arc length.…”

Section: Introductionmentioning

confidence: 99%

Form-Finding Analysis of a Class 2 Tensegrity Robot

et al. 2019

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In this paper, a new form-finding analysis methodology for a class 2 tensegrity robot is proposed. The methodology consists of two steps: first, the analysis of the possible geometric configurations of the robot is carried out through the results of the kinematic position analysis; and, second, from the static analysis, the equilibrium positions of the robot are found, which represents its workspace. Both kinematics and static analysis are resolved in a closed-form using basic tools of linear algebra instead of the strategies used in literature. Four numerical experiments are presented using the finite element analysis software ANSYS c . Additionally, a comparison between the results of the form-finding analysis methodology proposed and the ANSYS c results is presented.

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“…First, force equilibrium was used to demonstrate solution redundancy by Giannaccini et al (2018). Though the position state was ultimately found experimentally and then through kinematics (Hao et al, 2018), this approach identifies a fundamental capability of the arm structure. Second, Xu and Simaan (2010) developed a static model of a cable-driven NiTi arm using equilibrium on the end plate, similar to the approach that will be used here.…”

Section: Introductionmentioning

confidence: 99%

A generalizable equilibrium model for bending soft arms with longitudinal actuators

Olson

Chow

Nicolai

et al. 2019

The International Journal of Robotics Research

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Current models of bending in soft arms are formulated in terms of experimentally determined, arm-specific parameters, which cannot evaluate fundamental differences in soft robot arm design. Existing models are successful at improving control of individual arms but do not give insight into how the structure of the arm affects the arm’s capabilities. For example, omnidirectional soft robot arms most frequently have three parallel actuators, but may have four or more, while common biological arms, including octopuses, have tens of distinct longitudinal muscle bundles. This article presents a quasi-static analytical model of soft arms bent with longitudinal actuators, based on equilibrium principles and assuming an unknown neutral axis location. The model is presented as a generalizable framework and specifically implemented for an arm with [Formula: see text] fluid-driven actuators, a subset of which are pressurized to induce a bend with a certain curvature and direction. The presented implementation is validated experimentally using planar (2D) and spatial (3D) bends. The planar model is used to initially estimate pressure for a closed-loop curvature control system and to bound the accessible configurations for a rapidly-exploring random trees (RRT) motion planner. A three-segment planar arm is demonstrated to navigate along a planned trajectory through a gap in a wall. Finally, the model is used to explore how the arm morphology affects maximum curvature and directional resolution. This research analytically connects soft arm structure and actuator behavior to unloaded arm performance, and the results may be used to methodically design soft robot arms.

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Design and control of a novel variable stiffness soft arm

Cited by 25 publications

References 33 publications

Stiffness Analysis of a Pneumatic Soft Manipulator Based on Bending Shape Prediction

Stiffness Analysis of a Pneumatic Soft Manipulator Based on Bending Shape Prediction

Form-Finding Analysis of a Class 2 Tensegrity Robot

A generalizable equilibrium model for bending soft arms with longitudinal actuators

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