Minimally designed thermo-magnetic dual responsive soft robots for complex applications.

The fabrication of thermo-magnetic dual-responsive soft robots often requires intricate designs to implement complex locomotion patterns and utilize the implemented responsive behaviors. This work demonstrates a minimally designed soft robot based on poly-N-isopropylacrylamide (pNIPAM) and ferromagnetic particles, showcasing excellent control over both thermo- and magnetic responses. Free radical polymerization enables the magnetic particles to be entrapped homogeneously within the polymeric network. The integration of magnetic shape programming and temperature response allows the robot to perform various tasks including shaping, locomotion, pick-and-place, and release maneuvers of objects using independent triggers. The robot can be immobilized in a gripping state through magnetic actuation, and a subsequent increase in temperature transitions the robot from a swollen to a collapsed state. The temperature switch enables the robot to maintain a secured configuration while executing other movements via magnetic actuation. This approach offers a straightforward yet effective solution for achieving full control over both stimuli in dual-responsive soft robotics.

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.

A Magnetic Bio-Inspired Soft Carrier as a Temperature-Controlled Gastrointestinal Drug Delivery System.

Currently, gastrointestinal bleeding in the colon wall and the small bowel is diagnosed and treated with endoscopes. However, the locations of this condition are often problematic to treat using traditional flexible and tethered tools. New studies commonly consider untethered devices for solving this problem. However, there still exists a gap in the extant literature, and more research is needed to diagnose and deliver drugs in the lower gastrointestinal tract using soft robotic carriers. This paper discusses the development of an untethered, magnetically-responsive bio-inspired soft carrier. A molding process is utilized to produce prototypes from Diisopropylidene-1,6-diphenyl-1,6-hexanediol-based Polymer with Ethylene Glycol Dimethacrylate (DiAPLEX) MP-3510 - a shape memory polymer with a low transition temperature to enable the fabrication of these carriers. The soft carrier design is validated through simulation results of deformation caused by magnetic elements embedded in the carrier in response to an external field. The thermal responsiveness of the fabricated prototype carriers is assessed ex vivo and in a phantom. The results indicate a feasible design capable of administering drugs to a target inside a phantom of a large intestine. The soft carrier introduces a method for the controlled release of drugs by utilizing the rubbery modulus of the polymer and increasing the recovery force through magnetic actuation.

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.

Correction: Dynamic modeling of soft continuum manipulators using lie group variational integration.

[This corrects the article DOI: 10.1371/journal.pone.0236121.].

Dynamic modeling of soft continuum manipulators using lie group variational integration.

This paper presents the derivation and experimental validation of algorithms for modeling and estimation of soft continuum manipulators using Lie group variational integration. Existing approaches are generally limited to static and quasi-static analyses, and are not sufficiently validated for dynamic motion. However, in several applications, models need to consider the dynamical behavior of the continuum manipulators. The proposed modeling and estimation formulation is obtained from a discrete variational principle, and therefore grants outstanding conservation properties to the continuum mechanical model. The main contribution of this article is the experimental validation of the dynamic model of soft continuum manipulators, including external torques and forces (e.g., generated by magnetic fields, friction, and the gravity), by carrying out different experiments with metal rods and polymer-based soft rods. To consider dissipative forces in the validation process, distributed estimation filters are proposed. The experimental and numerical tests also illustrate the algorithm's performance on a magnetically-actuated soft continuum manipulator. The model demonstrates good agreement with dynamic experiments in estimating the tip position of a Polydimethylsiloxane (PDMS) rod. The experimental results show an average absolute error and maximum error in tip position estimation of 0.13 mm and 0.58 mm, respectively, for a manipulator length of 60.55 mm.