Locally Addressable Energy Efficient Actuation of Magnetic Soft Actuator Array Systems.

Advances in magnetoresponsive composites and (electro-)magnetic actuators have led to development of magnetic soft machines (MSMs) as building blocks for small-scale robotic devices. Near-field MSMs offer energy efficiency and compactness by bringing the field source and effectors in close proximity. Current challenges of near-field MSM are limited programmability of effector motion, dimensionality, ability to perform collaborative tasks, and structural flexibility. Herein, a new class of near-field MSMs is demonstrated that combines microscale thickness flexible planar coils with magnetoresponsive polymer effectors. Ultrathin manufacturing and magnetic programming of effectors is used to tailor their response to the nonhomogeneous near-field distribution on the coil surface. The MSMs are demonstrated to lift, tilt, pull, or grasp in close proximity to each other. These ultrathin (80 µm) and lightweight (100 gm-2 ) MSMs can operate at high frequency (25 Hz) and low energy consumption (0.5 W), required for the use of MSMs in portable electronics.

Magnetic Soft Helical Manipulators with Local Dipole Interactions for Flexibility and Forces.

Magnetic continuum manipulators (MCMs) are a class of continuum robots that can be actuated without direct contact by an external magnetic field. MCMs operating in confined workspaces, such as those targeting medical applications, require flexible magnetic structures that contain combinations of magnetic components and polymers to navigate long and tortuous paths. In cylindrical MCM designs, a significant trade-off exists between magnetic moment and bending flexibility as the ratio between length and diameter decreases. In this study, we propose a new MCM design framework that enables increasing diameter without compromising on flexibility and magnetic moment. Magnetic soft composite helices constitute bending regions of the MCM and are separated by permanent ring magnets. Local dipole interactions between the permanent magnets can reduce bending stiffness, depending on their size and spacing. For the particular segment geometry presented herein, the local dipole interactions result in a 31% increase in angular deflection of composite helices inside an external magnetic field, compared to helices without local interactions. In addition, we demonstrate fabrication, maneuverability, and example applications of a multisegment MCM in a phantom of the abdominal aorta, such as passing contrast dye and guidewires.

A Recurrent Neural-Network-Based Real-Time Dynamic Model for Soft Continuum Manipulators.

This paper introduces and validates a real-time dynamic predictive model based on a neural network approach for soft continuum manipulators. The presented model provides a real-time prediction framework using neural-network-based strategies and continuum mechanics principles. A time-space integration scheme is employed to discretize the continuous dynamics and decouple the dynamic equations for translation and rotation for each node of a soft continuum manipulator. Then the resulting architecture is used to develop distributed prediction algorithms using recurrent neural networks. The proposed RNN-based parallel predictive scheme does not rely on computationally intensive algorithms; therefore, it is useful in real-time applications. Furthermore, simulations are shown to illustrate the approach performance on soft continuum elastica, and the approach is also validated through an experiment on a magnetically-actuated soft continuum manipulator. The results demonstrate that the presented model can outperform classical modeling approaches such as the Cosserat rod model while also shows possibilities for being used in practice.