As a result of the difficulties brought by COVID-19 and its associated lockdowns, many individuals and companies have turned to robots in order to overcome the challenges of the pandemic. Compared with traditional human labor, robotic and autonomous systems have advantages such as an intrinsic immunity to the virus and an inability for human-robot-human spread of any disease-causing pathogens, though there are still many technical hurdles for the robotics industry to overcome. This survey comprehensively reviews over 200 reports covering robotic systems which have emerged or have been repurposed during the past several months, to provide insights to both academia and industry. In each chapter, we cover both the advantages and the challenges for each robot, finding that robotics systems are overall apt solutions for dealing with many of the problems brought on by COVID-19, including: diagnosis, screening, disinfection, surgery, telehealth, care, logistics, manufacturing and broader interpersonal problems unique to the lockdowns of the pandemic. By discussing the potential new robot capabilities and fields they applied to, we expect the robotics industry to take a leap forward due to this unexpected pandemic.

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Bioprinting of complex cell-laden tissue constructs that mimic the human vascular tissue structure.

The direct electrostatic printing of highly viscous thermoplastic polymers onto movable collectors, a process known as melt electrospinning writing (MEW), has significant potential as an additive biomanufacturing (ABM) technology. MEW has the hitherto unrealized potential of fabricating three-dimensional (3D) porous interconnected fibrous mesh-patterned scaffolds in conjunction with cellular-relevant fiber diameters and interfiber distances without the use of cytotoxic organic solvents. However, this potential cannot be readily fulfilled owing to the large number and complex interplay of the multivariate independent parameters of the melt electrospinning process. To overcome this manufacturing challenge, dimensional analysis is employed to formulate a “Printability Number” (NPR), which correlates with the dimensionless numbers arising from the nondimensionalization of the governing conservation equations of the electrospinning process and the viscoelasticity of the polymer melt. This analysis suggests that the applied voltage potential (Vp), the volumetric flow rate (Q), and the translational stage speed (UT) are the most critical parameters toward efficient printability. Experimental investigations using a poly(ε-caprolactone) (PCL) melt reveal that any perturbations arising from an imbalance between the downstream pulling forces and the upstream resistive forces can be eliminated by systematically tuning Vp and Q for prescribed thermal conditions. This, in concert with appropriate tuning of the translational stage speed, enables steady-state equilibrium conditions to be achieved for the printing of microfibrous woven meshes with precise and reproducible geometries.

A wearable surgical navigation system is developed for intraoperative imaging of surgical margin in cancer resection surgery. The system consists of an excitation light source, a monochromatic CCD camera, a host computer, and a wearable headset unit in either of the following two modes: head-mounted display (HMD) and Google glass. In the HMD mode, a CMOS camera is installed on a personal cinema system to capture the surgical scene in real-time and transmit the image to the host computer through a USB port. In the Google glass mode, a wireless connection is established between the glass and the host computer for image acquisition and data transport tasks. A software program is written in Python to call OpenCV functions for image calibration, co-registration, fusion, and display with augmented reality. The imaging performance of the surgical navigation system is characterized in a tumor simulating phantom. Image-guided surgical resection is demonstrated in an ex vivo tissue model. Surgical margins identified by the wearable navigation system are co-incident with those acquired by a standard small animal imaging system, indicating the technical feasibility for intraoperative surgical margin detection. The proposed surgical navigation system combines the sensitivity and specificity of a fluorescence imaging system and the mobility of a wearable goggle. It can be potentially used by a surgeon to identify the residual tumor foci and reduce the risk of recurrent diseases without interfering with the regular resection procedure.

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Bioprinting is an emerging and promising technique for fabricating 3D cell-laden constructs for various biomedical applications. In this paper, we employed 3D bioprinted GelMA-based models to investigate the trophoblast cell invasion phenomenon, enabling studies of key placental functions. Initially, a set of optimized material and process parameters including GelMA concentration, UV crosslinking time and printing configuration were identified by systematic, parametric study. Following this, a multiple-ring model (2D multi-ring model) was tested with the HTR-8/SVneo trophoblast cell line to measure cell movement under the influence of EGF (chemoattractant) gradients. In the multi-ring model, the cell front used as a cell invasion indicator moves at a rate of 85 ± 33 µm/day with an EGF gradient of 16 µM. However, the rate was dramatically reduced to 13 ± 5 µm/day, when the multi-ring model was covered with a GelMA layer to constrain cells within the 3D environment (3D multi-ring model). Due to the geometric and the functional limitations of multi-ring model, a multi-strip model (2D multi-strip model) was developed to investigate cell movement in the presence and absence of the EGF chemoattractant. The results show that in the absence of an overlying cell-free layer of GelMA, movement of the cell front shows no significant differences between control and EGF-stimulated rates, due to the combination of migration and proliferation at high cell density (6 × 106 cells/ml) near the GelMA surface. When the model was covered by a layer of GelMA (3D multi-strip model) and migration was excluded, EGF-stimulated cells showed an invasion rate of 21 ± 3 µm/day compared to the rate for unstimulated cells, of 5 ± 4 µm/day. The novel features described in this report advance the use of the 3D bioprinted placental model as a practical tool for not only measurement of trophoblast invasion but also the interaction of invading cells with other tissue elements.

Currently, bioprinting high cellular fractions in bio-inks represents a critical step towards engineered tissue models with enhanced biological relevance. However, precise spatiotemporal mapping of high cell densities within hydrogel materials represents a significant challenge. To address these needs and challenges, this paper advances a systematic multidimensional analytical framework to quantitatively determine the spatial variations in cell density and temporal evolution of cell redistribution phenomena within bioprinted cell-laden fiber-based constructs as a function of the complex interplay of the various processing parameters for an alginate-gelatin hydrogel material system. For a one dimensional analysis, fibers printed at high relative viscosities exhibit large contact angles in the crosssectional plane with a high degree of cell dispersion (D d =96.8±6.27%). Conversely, fibers printed at low relative viscosities exhibit small contact angles with cells coalescing towards the fiber midline (D d =76.3±4.58%). The observed in-process redistribution of cells is attributed to the flow topology inside the needle tip. The precise mechanism is governed by the temperature-dependent viscoplastic material properties as demonstrated numerically using the Herschel-Bulkley model. In the 2D analysis, the printed grid structures yield differences in local cell densities between the strut and cross regions within the fibers. At low relative viscosities, cells aggregate in regions where two overlapping fibers fuse together, yielding a high cell density ratio (1.79±0.04) between the cross and strut regions. However, at high relative viscosities, the cell density ratio decreases (0.96±0.03). In the 3D analysis, due to gravity and extrusion process effects, initially uniform bio-ink cell distributions within bio-inks are redistributed as a function of printing time, yielding quantitative increases in cell density for the initial layers, followed by quantitative decreases in the subsequent layers. Finally, a time course incubation study of the 3D bioprinted cell-laden construct reveals a time-dependent increase in cell density owing to proliferation that accelerates the material degradation.