Search for: All records

Controlling the deformation of a soft body has potential applications in fields requiring precise control over the shape of the body. Areas such as medical robotics can use the shape control of soft robots to repair aneurysms in humans, deliver medicines within the body, among other applications. However, given known external loading, it is usually not possible to deform a soft body into arbitrary shapes if it is fabricated using only a single material. In this work, we propose a new physics-based method for the computational design of soft hyperelastic bodies to address this problem. The method takes as input an undeformed shape of a body, a specified external load, and a user desired final shape. It then solves an inverse problem in design using nonlinear optimization subject to physics constraints. The nonlinear program is solved using a gradient-based interior-point method. Analytical gradients are computed for efficiency. The method outputs fields of material properties which can be used to fabricate a soft body. A body fabricated to match this material field is expected to deform into a user-desired shape, given the same external loading input. Two regularizers are used to ascribea prioricharacteristics of smoothness and contrast, respectively, to the spatial distribution of material fields. The performance of the method is tested on three example cases in silico.

 

Many natural organisms, such as fungal hyphae and plant roots, grow at their tips, enabling the generation of complex bodies composed of natural materials as well as dexterous movement and exploration. Tip growth presents an exemplary process by which materials synthesis and actuation are coupled, providing a blueprint for how growth could be realized in a synthetic system. Herein, we identify three underlying principles essential to tip-based growth of biological organisms: a fluid pressure driving force, localized polymerization for generating structure, and fluid-mediated transport of constituent materials. In this work, these evolved features inspire a synthetic materials growth process called extrusion by self-lubricated interface photopolymerization (E-SLIP), which can continuously fabricate solid profiled polymer parts with tunable mechanical properties from liquid precursors. To demonstrate the utility of E-SLIP, we create a tip-growing soft robot, outline its fundamental governing principles, and highlight its capabilities for growth at speeds up to 12 cm/min and lengths up to 1.5 m. This growing soft robot is capable of executing a range of tasks, including exploration, burrowing, and traversing tortuous paths, which highlight the potential for synthetic growth as a platform for on-demand manufacturing of infrastructure, exploration, and sensing in a variety of environments. 

Surgeons are human: their best possible performance is limited by their neurophysiology. What if an inoperable patient’s condition demands surgical treatment that exceeds such human performance limits? Can precision surgical robots help surgeons surpass such fundamental human neurophysiological limits? This article employs the Steering law to proposes a quantitative framework and benchmark tasks to evaluate the feasibility of a handheld surgical tool for meeting the quantified speed and accuracy requirements of a clinical need in non-contact interactions that exceed human limitations. Example use cases of such interactions in common surgical scenarios are presented. Preliminary results from a straight-line tracking task with and without computer assistance demonstrate the proposed framework in the context of falling short of a clinical speed/accuracy need. The framework is then used to articulate specifications for additional technology candidates to successfully exceed the speed and accuracy characteristics of the modality used. 

Background: Reliable and valid assessments of the visual endpoints of aesthetic surgery procedures are needed. Currently, most assessments are based on the opinion of patients and their plastic surgeons. The objective of this research was to analyze the reliability of crowdworkers assessing de-identified photographs using a validated scale that depicts lower facial aging. Methods: Twenty photographs of the facial nasolabial region of various non-identifiable faces were obtained for which various degrees of facial aging were present. Independent crowds of 100 crowd workers were tasked with assessing the degree of aging using a photograph numeric scale. Independent groups of crowdworkers were surveyed at 4 different times (weekday daytime, weekday nighttime, weekend daytime, weekend nighttime), once a week for 2 weeks. Results: Crowds assessing midface region photographs had an overall correlation of R = 0.979 (weekday daytime R = 0.991; weekday nighttime R = 0.985; weekend daytime R = 0.997; weekend nighttime R = 0.985). Bland−Altman test for test-retest agreement showed a normal distribution of assessments over the various times tested, with the differences in the majority of photographs being within 1 SD of the average difference in ratings. Conclusions: Crowd assessments of facial aging in de-identified photographs displayed very strong concordance with each other, regardless of time of day or week. This shows promise toward obtaining reliable assessments of pre and postoperative results for aesthetic surgery procedures. More work must be done to quantify the reliability of assessments for other pretreatment states or the corresponding results following treatment.