Morphology and Tension Perception of Cable-Driven Continuum Robots

Liu, Zhongzhen; Cai, Zhiqin; Peng, Haijun; Zhang, Xingang; Wu, Zhigang

doi:10.1109/tmech.2022.3198093

Cited by 27 publications

(7 citation statements)

References 32 publications

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“…By assuming that the static force contributions are almost constant and dominate the dynamic ones, we have τ y ≈ constant. In this way, (14) becomes an algebraic relationship between q y and the variables q x , α, and thus, it can be used to reduce the number of DoF in the model.…”

Section: Reduced Dynamic Modelmentioning

confidence: 99%

“…To formally derive the simplified model, we define the reduced configuration vector in r = [q x α] , and use (14) to express the transformation between r and q through…”

Section: Reduced Dynamic Modelmentioning

confidence: 99%

“…In some cases, like in cable-driven soft robots, the sensing feature can be directly integrated within the same component performing actuation [13]. For instance, in [14] the configuration and tension of a cable-driven soft robot were estimated via the actuator lengths, and reconstructed through motor-level sensors. The approach produces accurate sensing, but requires detailed nonlinear modeling and calibration of friction and hysteresis, as well as a custom and rather complex real-time numerical solving strategy.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Sensorless Proprioception in Multi-DoF Dielectric Elastomer Soft Robots via System-Level Self-Sensing

Prechtl,

Baltes,

Flaßkamp

et al. 2024

IEEE/ASME Trans. Mechatron.

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Proprioception in soft robots remains an ongoing challenge, owing to practical issues such as tight sensor integration while maintaining mechanical compliance. Soft robots based on dielectric elastomer (DE) technology could provide a compelling answer to these challenges, due to the inherent flexibility and compliance of such transducers as well as their ability to simultaneously work as actuators and sensors, i.e., self-sensing. In this work, we propose a novel real-time self-sensing scheme for DE soft robotic systems. By combining an actuatorlevel recursive least squares identification with an extended Kalman filter, our architecture provides an estimation of the mechanical state of the structure without requiring additional electromechanical sensors, solely relying on electrical measurements performed on the DEs during high voltage actuation. Experimental validation, conducted on a DE soft robot prototype, reveals that the proposed solution reconstructs the system state during actuation in a robust and accurate way, and under various external loading conditions.

show abstract

Section: Reduced Dynamic Modelmentioning

confidence: 99%

“…To formally derive the simplified model, we define the reduced configuration vector in r = [q x α] , and use (14) to express the transformation between r and q through…”

Section: Reduced Dynamic Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Sensorless Proprioception in Multi-DoF Dielectric Elastomer Soft Robots via System-Level Self-Sensing

Prechtl,

Baltes,

Flaßkamp

et al. 2024

IEEE/ASME Trans. Mechatron.

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show abstract

“…[4] The existing continuum robots can be classified into three typical categories in terms of actuation, namely, the pneumaticdriven, [5] smart material-driven, [6] and cable-driven robots. [7] Pneumatic-driven continuum robots, which are powered by compressed gas or fluid, cannot be used to make compact and lightweight robotic systems. Smart material-driven robots have also limited output force that impedes their usability in human environments.…”

Section: Introductionmentioning

confidence: 99%

“…[ 4 ] The existing continuum robots can be classified into three typical categories in terms of actuation, namely, the pneumatic‐driven, [ 5 ] smart material‐driven, [ 6 ] and cable‐driven robots. [ 7 ]…”

Section: Introductionmentioning

confidence: 99%

In Situ Reconfigurable Continuum Robot with Varying Curvature Enabled by Programmable Tensegrity Building Blocks

Zhang¹,

Shi²,

Huang³

et al. 2023

Advanced Intelligent Systems

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Reconfigurable continuum robots exhibit programmable interaction capability, enabling them to cope with challenges poorly addressed by conventional rigid robots. However, the regulation of the module type and/or sequence may result in time‐consuming and labor‐intensive problems. Therefore, in situ reconfiguration schemes are required to develop in a simple yet robust solution for continuum robot design. Herein, inspired by the structure characteristics of the seahorse tail, an original template based on a tensegrity building block (TBB) for creating an in situ reconfigurable continuum robotic paradigm is proposed. As the length of the stretchable struts in the TBB could be programmed, five typical homologous types from the template are derived. Then, ten TBBs into a continuum robot are assembled and the multi‐body dynamic framework is employed to develop a mechanical model for predicting the profile after deformation. Theoretical predictions demonstrate that the robotic shape can be customized in situ by switching the type of TBBs, without disassembling the robot. Furthermore, the tailored continuum robotic configurations are applied to conformally interact with the varying‐curvature objects. The experimental results suggest that the proposed programmable template offers a facile and rapid reconfiguration scheme for the continuum robots, which greatly improves the robotic interaction capability.

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A Soft Collaborative Robot for Contact‐based Intuitive Human Drag Teaching

Gong,

Li,

et al. 2024

Advanced Science

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Soft material‐based robots, known for their safety and compliance, are expected to play an irreplaceable role in human‐robot collaboration. However, this expectation is far from real industrial applications due to their complex programmability and poor motion precision, brought by the super elasticity and large hysteresis of soft materials. Here, a soft collaborative robot (Soft Co‐bot) with intuitive and easy programming by contact‐based drag teaching, and also with exceptional motion repeatability (< 0.30% of body length) and ultra‐low hysteresis (< 2.0%) is reported. Such an unprecedented capability is achieved by a biomimetic antagonistic design within a pneumatic soft robot, in which cables are threaded to servo motors through tension sensors to form a self‐sensing system, thus providing both precise actuation and dragging‐aware collaboration. Hence, the Soft Co‐bots can be first taught by human drag and then precisely repeat various tasks on their own, such as electronics assembling, machine tool installation, etc. The proposed Soft Co‐bots exhibit a high potential for safe and intuitive human‐robot collaboration in unstructured environments, promoting the immediate practical application of soft robots.

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Morphology and Tension Perception of Cable-Driven Continuum Robots

Cited by 27 publications

References 32 publications

Sensorless Proprioception in Multi-DoF Dielectric Elastomer Soft Robots via System-Level Self-Sensing

Sensorless Proprioception in Multi-DoF Dielectric Elastomer Soft Robots via System-Level Self-Sensing

In Situ Reconfigurable Continuum Robot with Varying Curvature Enabled by Programmable Tensegrity Building Blocks

A Soft Collaborative Robot for Contact‐based Intuitive Human Drag Teaching

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