Active-Cooling-in-the-Loop Controller Design and Implementation for an SMA-Driven Soft Robotic Tentacle

An, Xin; Cui, Yafeng; Sun, Hao; Shao, Qi; Zhao, Huichan

doi:10.1109/tro.2023.3234801

Cited by 24 publications

(11 citation statements)

References 46 publications

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“…Figure 9 presents the experimental results of tracking control for the PSBA. Note that the initial bending angle was set at 30 • for two primary reasons: (1) The soft material tends to naturally bend at an angle of roughly 30 • due to changes in its properties after multiple bending motions. (2) The requirement of the PSBA for pre-filling with a starting pressure of approximately 0.5 bar to maintain stability, which experimentally corresponds to a bending angle close to 30 • .…”

Section: Comparative Experiments and Resultsmentioning

confidence: 99%

Model-based linear control of nonlinear pneumatic soft bending actuators

Wang,

Xu,

Lai

et al. 2024

Smart Mater. Struct.

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Advanced model-based control techniques hold great promise for the precise control of pneumatic soft bending actuators (PSBAs) with strong nonlinearities. However, most previous controllers were designed in a cumbersome nonlinear form. Considering the simplicity of linear system theory, this paper presents a novel perspective on using model-based linear control to handle nonlinear PSBAs, and for the first time, summarizes two methodologies, global linearization and pseudo-linear construction. Derived from them, Koopman-based and hysteresis-based linear control approaches are proposed, respectively. For the former, a novel fusion prediction equation is developed to build a high-fidelity Koopman model, realizing global linearization, and then the linear model predictive control (MPC) is deployed. For the latter, the inverse of the generalized Prandtl-Ishlinskii (GPI) model cascades with the PSBA to construct a pseudo-linear system, eliminating the asymmetric hysteresis, which activates the linear proportional–integral–derivative (PID) control. It is worth noting that the above two are based on data-driven models adapted to various PSBAs with material and structural customization. Finally, the two model-based linear control approaches are verified and compared through a series of experiments. The results show that the proposed linear controls, with more concise designs, achieve comparable or even superior performance than nonlinear controls.

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Section: Comparative Experiments and Resultsmentioning

confidence: 99%

Model-based linear control of nonlinear pneumatic soft bending actuators

Wang,

Xu,

Lai

et al. 2024

Smart Mater. Struct.

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show abstract

“…Overall, the output of the attitude control or object tracking serves as the input of the PID control procedure to generate the required current. Compared to existing controllers for similar SMA‐driven actuators, [ 27 ] the vector‐PID controller contains only one PID controller channel and the control algorithm is simpler. In such extreme environments as the deep sea, the performance of electronic devices is typically unstable.…”

Section: Control Schemementioning

confidence: 99%

“…[ 23 ] Thus, active cooling is typically demonstrated to increase the bandwidth. [ 27 ] However, the addition of other devices will complicate the system. Instead, our control method can help accelerate the recovery process without adding other devices.…”

Section: Control Schemementioning

confidence: 99%

A Bioinspired Shape Memory Alloy Based Soft Robotic System for Deep‐Sea Exploration

Xu,

Zhuo,

Fan

et al. 2024

Advanced Intelligent Systems

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Developing robots integrating sensors, actuators, and computational capabilities for deep‐sea exploration is challenging. Nature often offers innovative solutions to complex problems, and in this context, inspiration is drawn from the remarkable abilities of deep‐sea snails, specifically their unique tentacles, often referred to as “eyestalks” due to the presence of an eye at their tip. Herein, “DeepStalk,” a soft robot designed for deep‐sea exploration, is introduced, utilizing three shape memory alloys (SMAs) springs that mimic the three tentacle flexor muscles of deep‐sea snails. Overall, DeepStalk incorporates sensory, actuation, and control modules for operation under high hydrostatic pressure. To achieve precise control of its orientation in 3D space, a simple and reliable vector‐PID controller is developed. Remarkably, the robot successfully maintains its desired bending attitude even at 30 MPa hydrostatic pressure, achieved through the Joule heating of SMA springs. Furthermore, DeepStalk demonstrates the capability to track moving objects underwater, showcasing its potential application in challenging environments at depths of up to 20 MPa. This marks the first attempt for soft robots to integrate sensor, actuator, and control modules capable of complex tasks under high hydrostatic pressure. This innovative research advances integrated soft robotic systems for deep‐sea exploration field.

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“…designed a 3-piece SMA spring-driven elastic soft robot tentacle, as shown in Fig. 9 F. Efficient motion tracking of predefined trajectories and random trajectories was achieved by coordinating the bending and oscillating motions through the controller [ 156 ].…”

Section: Integrated Actuation and Sensingmentioning

confidence: 99%

“…(F) Flexible soft robot tentacles with an integrated motion capture system actuated by 3 SMA springs. Reproduced with permission from [ 156 ].…”

Section: Integrated Actuation and Sensingmentioning

confidence: 99%

Integrated Actuation and Sensing: Toward Intelligent Soft Robots

Zhou,

Li,

Wang

et al. 2024

Cyborg Bionic Syst

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Soft robotics has received substantial attention due to its remarkable deformability, making it well-suited for a wide range of applications in complex environments, such as medicine, rescue operations, and exploration. Within this domain, the interaction of actuation and sensing is of utmost importance for controlling the movements and functions of soft robots. Nonetheless, current research predominantly focuses on isolated actuation and sensing capabilities, often neglecting the critical integration of these 2 domains to achieve intelligent functionality. In this review, we present a comprehensive survey of fundamental actuation strategies and multimodal actuation while also delving into advancements in proprioceptive and haptic sensing and their fusion. We emphasize the importance of integrating actuation and sensing in soft robotics, presenting 3 integration methodologies, namely, sensor surface integration, sensor internal integration, and closed-loop system integration based on sensor feedback. Furthermore, we highlight the challenges in the field and suggest compelling directions for future research. Through this comprehensive synthesis, we aim to stimulate further curiosity among researchers and contribute to the development of genuinely intelligent soft robots.

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Active-Cooling-in-the-Loop Controller Design and Implementation for an SMA-Driven Soft Robotic Tentacle

Cited by 24 publications

References 46 publications

Model-based linear control of nonlinear pneumatic soft bending actuators

Model-based linear control of nonlinear pneumatic soft bending actuators

A Bioinspired Shape Memory Alloy Based Soft Robotic System for Deep‐Sea Exploration

Integrated Actuation and Sensing: Toward Intelligent Soft Robots

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