Learning to Control a Three-Dimensional Ferrofluidic Robot.

In recent years, ferrofluids have found increased popularity as a material for medical applications, such as ocular surgery, gastrointestinal surgery, and cancer treatment, among others. Ferrofluidic robots are multifunctional and scalable, exhibit fluid properties, and can be controlled remotely; thus, they are particularly advantageous for such medical tasks. Previously, ferrofluidic robot control has been achieved via the manipulation of handheld permanent magnets or in current-controlled electromagnetic fields resulting in two-dimensional position and shape control and three-dimensional (3D) coupled position-shape or position-only control. Control of ferrofluidic liquid droplet robots poses a unique challenge where model-based control has been shown to be computationally limiting. Thus, in this study, a model-free control method is chosen, and it is shown that the task of learning optimal control parameters for ferrofluidic robot control can be performed using machine learning. Particularly, we explore the use of Bayesian optimization to find optimal controller parameters for 3D pose control of a ferrofluid droplet: its centroid position, stretch direction, and stretch radius. We demonstrate that the position, stretch direction, and stretch radius of a ferrofluid droplet can be independently controlled in 3D with high accuracy and precision, using a simple control approach. Finally, we use ferrofluidic robots to perform pick-and-place, a lab-on-a-chip pH test, and electrical switching, in 3D settings. The purpose of this research is to expand the potential of ferrofluidic robots by introducing full pose control in 3D and to showcase the potential of this technology in the areas of microassembly, lab-on-a-chip, and electronics. The approach presented in this research can be used as a stepping-off point to incorporate ferrofluidic robots toward future research in these areas.

Advances in Implantable Microelectrode Array Insertion and Positioning.

OBJECTIVES: Microelectrode arrays offer a means to probe the functional circuitry of the brain and the promise of cortical neuroprosthesis for individuals suffering from paralysis or limb loss. These devices are typically comprised of one or more shanks incorporating microelectrode sites, where the shanks are positioned by inserting the devices along a straight path that is normal to the brain surface. The lack of consistent long-term chronic recording technology has driven interest in novel probe design and approaches that go beyond the standard insertion approach that is limited to a single velocity or axis. This review offers a description of typical approaches and associated limitations and surveys emergent methods for implantation of microelectrode arrays, in particular those new approaches that leverage embedded microactuators and extend the insertion direction beyond a single axis. MATERIALS AND METHODS: This review paper surveys the current technologies that enable probe implantation, repositioning, and the capability to record/stimulate from a tissue volume. A comprehensive literature search was performed using PubMed, Web of Science, and Google Scholar. RESULTS: There has been substantial innovation in the development of microscale and embedded technology that enables probe repositioning to maintain quality recordings in the brain. Innovations in material science have resulted in novel strategies for deployable structures that can record from or stimulate a tissue volume. Moreover, new developments involving magnetically steerable catheters and needles offer an alternative approach to "pull" rather than "push" a probe into the tissue. CONCLUSION: We envision the emergence of a new generation of probes and insertion methodologies for neuromodulation applications that enable reliable chronic performance from devices that can be positioned virtually anywhere in the brain.

Heterogeneous Hydrogel Structures with Spatiotemporal Reconfigurability using Addressable and Tunable Voxels.

Stimuli-responsive hydrogels can sense environmental cues and change their volume accordingly without the need for additional sensors or actuators. This enables a significant reduction in the size and complexity of resulting devices. However, since the responsive volume change of hydrogels is typically uniform, their robotic applications requiring localized and time-varying deformations have been challenging to realize. Here, using addressable and tunable hydrogel building blocks-referred to as soft voxel actuators (SVAs)-heterogeneous hydrogel structures with programmable spatiotemporal deformations are presented. SVAs are produced using a mixed-solvent photopolymerization method, utilizing a fast reaction speed and the cononsolvency property of poly(N-isopropylacrylamide) (PNIPAAm) to produce highly interconnected hydrogel pore structures, resulting in tunable swelling ratio, swelling rate, and Young's modulus in a simple, one-step casting process that is compatible with mass production of SVA units. By designing the location and swelling properties of each voxel and by activating embedded Joule heaters in the voxels, spatiotemporal deformations are achieved, which enables heterogeneous hydrogel structures to manipulate objects, avoid obstacles, generate traveling waves, and morph to different shapes. Together, these innovations pave the way toward tunable, untethered, and high-degree-of-freedom hydrogel robots that can adapt and respond to changing conditions in unstructured environments.

Materials, Actuators, and Sensors for Soft Bioinspired Robots.

Biological systems can perform complex tasks with high compliance levels. This makes them a great source of inspiration for soft robotics. Indeed, the union of these fields has brought about bioinspired soft robotics, with hundreds of publications on novel research each year. This review aims to survey fundamental advances in bioinspired soft actuators and sensors with a focus on the progress between 2017 and 2020, providing a primer for the materials used in their design.

A Shapeshifting Ferrofluidic Robot.

To create a miniature shapeshifting robot capable of controlled movement, subdivision, regeneration, passage through small channels, engulfment of particles, object manipulation, and flow manipulation, a droplet of magnetically responsive ferrofluid is used. The ferrofluidic robot can achieve the aforementioned functions when both its position and shape are controlled using a custom electromagnetic field generation system. It is demonstrated that the proposed robot can perform these functions with submillimeter and subdegree error. A robot having these capabilities can remotely perform medical and microassembly tasks requiring fine dexterity that are currently difficult or impossible.

Granular scaling laws for helically driven dynamics.

Exploration of granular physics for three-dimensional geometries interacting with deformable media is crucial for further understanding of granular mechanics and vehicle-terrain dynamics. A modular screw propelled vehicle is, therefore, designed for testing the accuracy of a novel helical granular scaling law in predicting vehicle translational velocity and power. A dimensional analysis is performed on the vehicle and screw pontoons. Two additional pontoon pairs of increased size and mass are determined from dimensional scalars. The power and velocity of these larger pairs are predicted by the smaller pair using the scaling relationships. All three sets are subjected to ten trials of five angular velocities ranging from 13.7 to 75.0 revolutions per minute in a high interlock lunar regolith analog derived from mining tailings. Experimental agreement for prediction of power (3-9% error) and translational velocity (2-12% error) are observed. A similar set of geometries is subjected to multibody dynamics and discrete element method cosimulations of Earth and lunar gravity to verify a gravity-dependent subset of the scaling laws. These simulations show agreement (under 5% error for all sets) and support law validity for gravity between Earth and lunar magnitude. These results support further expansion of granular scaling models to enable prediction for vehicle-terrain dynamics for a variety of environments and geometries.

Magnetic Needle Steering in Soft Phantom Tissue.

Needle steering is a technology for guiding needles around sensitive internal obstacles in minimally invasive surgery. Traditional techniques apply rotation at the base of a needle with an asymmetric tip, enabling steering through the redirection of radial forces. Magnetic steering of catheters and continuum manipulators is another technology that allows steering of a shaft in the body. Both of these techniques rely on mechanical or manual shaft advancement methods. Needle steering has not achieved widespread clinical use due to several limitations: 1- buckling and compression effects in the shaft and needle rotation cause excessive tissue damage; 2- torsion effects on the shaft and needle deflection at tissue boundaries lead to difficulty in control; and 3- restricted radius of curvature results in limited workspace. Magnetically steered catheters and continuum manipulators also suffer from limited curvature and the possibility of buckling. This paper proposes a novel needle steering method empowered by electromagnetic actuation that overcomes all of the aforementioned limitations, making it a promising option for further study toward healthcare applications.

Shape-programmable magnetic soft matter.

Shape-programmable matter is a class of active materials whose geometry can be controlled to potentially achieve mechanical functionalities beyond those of traditional machines. Among these materials, magnetically actuated matter is particularly promising for achieving complex time-varying shapes at small scale (overall dimensions smaller than 1 cm). However, previous work can only program these materials for limited applications, as they rely solely on human intuition to approximate the required magnetization profile and actuating magnetic fields for their materials. Here, we propose a universal programming methodology that can automatically generate the required magnetization profile and actuating fields for soft matter to achieve new time-varying shapes. The universality of the proposed method can therefore inspire a vast number of miniature soft devices that are critical in robotics, smart engineering surfaces and materials, and biomedical devices. Our proposed method includes theoretical formulations, computational strategies, and fabrication procedures for programming magnetic soft matter. The presented theory and computational method are universal for programming 2D or 3D time-varying shapes, whereas the fabrication technique is generic only for creating planar beams. Based on the proposed programming method, we created a jellyfish-like robot, a spermatozoid-like undulating swimmer, and an artificial cilium that could mimic the complex beating patterns of its biological counterpart.