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Category: robotics/AI

Composite membrane origami has been an efficient and effective method for constructing transformable mechanisms while considerably simplifying their design, fabrication, and assembly; however, its limited load-bearing capability has restricted its application potential. With respect to wheel design, membrane origami offers unique benefits compared with its conventional counterparts, such as simple fabrication, high weight-to-payload ratio, and large shape variation, enabling softness and flexibility in a kinematic mechanism that neutralizes joint distortion and absorbs shocks from the ground. Here, we report a transformable wheel based on membrane origami capable of bearing more than a 10-kilonewton load. To achieve a high payload, we adopt a thick membrane as an essential element and introduce a wireframe design rule for thick membrane accommodation. An increase in the thickness can cause a geometric conflict for the facet and the membrane, but the excessive strain energy accumulation is unique to the thickness increase of the membrane. Thus, the design rules for accommodating membrane thickness aim to address both geometric and physical characteristics, and these rules are applied to basic origami patterns to obtain the desired wheel shapes and transformation. The capability of the resulting wheel applied to a passenger vehicle and validated through a field test. Our study shows that membrane origami can be used for high-payload applications.

Origami has been a rich source of inspiration for art, education, and mathematics, and it has proven to be an efficient and effective method for realizing transformable structures in nature (1–3) and artificial systems (4–8). Composite membrane origami, the design technique based on the laminar composition of flexible membranes with rigid facet constraints, opens a new field for robotics by the transition from component assembly to lamination, which considerably simplifies design, fabrication, and assembly. This transition simplifies and speeds up fabrication and enables reaching size scales that were difficult to access before (9, 10). In addition, membrane origami provides a versatile shape-changing ability that has been exploited in various applications (11–15), and its applicability has been extended by additional design dimensions obtained from material characteristics such as softness and stretchability (16–19).

Beyond the aforementioned benefits, origami has been an effective design tool for constructing a high payload-to-weight structure, such as a honeycomb panel, by markedly increasing the buckling strength using unique geometric configurations (20, 21). Combining this feature with reconfigurability, various stiffness transition mechanisms have also been introduced (22–24). The rigidity of components is another important factor to secure high load capacity and closely related to the thickness. Origami design is, traditionally, a matter of organizing fold lines under fundamental and ideal assumptions—zero facet thickness and zero fold line width (25–27). However, in response to growing interest in origami-inspired applications that require load-bearing capability, various thickness accommodation methods have been introduced (28–30).

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Hydrogels are an exciting class of materials for new and emerging robotics. For example, actuators based on hydrogels have impressive deformability and responsiveness. Studies into hydrogels with autonomous locomotive abilities, however, are limited. Existing hydrogels achieve locomotion through the application of cyclical stimuli or chemical modifications. Here, we report the fabrication of active hydrogels with an intrinsic ability to move on the surface of water without operated stimuli for up to 3.5 hours. The active hydrogels were composed of hydrophobic and hydrophilic groups and underwent a dynamic wetting process to achieve spatial and temporal control of surface tension asymmetry. Using surface tension, the homogeneous active hydrogels propelled themselves and showed controlled locomotion on water, similar to common water striders.

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Continuous and controlled shape morphing is essential for soft machines to conform, grasp, and move while interacting safely with their surroundings. Shape morphing can be achieved with two-dimensional (2D) sheets that reconfigure into target 3D geometries, for example, using stimuli-responsive materials. However, most existing solutions lack the ability to reprogram their shape, face limitations on attainable geometries, or have insufficient mechanical stiffness to manipulate objects. Here, we develop a soft, robotic surface that allows for large, reprogrammable, and pliable shape morphing into smooth 3D geometries. The robotic surface consists of a layered design composed of two active networks serving as artificial muscles, one passive network serving as a skeleton, and cover scales serving as an artificial skin.

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Around a century ago when film stocks and photographs were first coming to light, they faced a number of challenges in capturing the essence of an image. In addition to the black and white limitation, photography and film methods also struggled to capture other various elements of the color spectrum, rendering many images of famous figures appearing differently than they may have actually looked.

Now, a new AI imaging technique uses color to restyle old photographs in a way that could almost pass for modern day photographs. This colorization method mitigates the main obstacles of cameras and lenses from the olden days—namely, the orthochromatic nature of those tools, meaning that the photo capture device in question incorporated all detected light into the image without discrimination. The inclusion of all of this light resulted in photos that appeared grainy and noisy, leading to renowned figures such as U.S. president Abraham Lincoln looking far older and wrinklier than he actually was.

These days, especially with the aid of computer graphics, more advanced photographic techniques have taken advantage of the fact that tends to penetrate the surface of human skin and illuminate the flesh from underneath. This illumination helps to eliminate extra noise and wrinkle marks that marred many images from the early 1900s.

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Whatever business a company may be in, software plays an increasingly vital role, from managing inventory to interfacing with customers. Software developers, as a result, are in greater demand than ever, and that’s driving the push to automate some of the easier tasks that take up their time.

Productivity tools like Eclipse and Visual Studio suggest snippets of code that developers can easily drop into their work as they write. These automated features are powered by sophisticated language models that have learned to read and write after absorbing thousands of examples. But like other deep learning models trained on big datasets without explicit instructions, language models designed for code-processing have baked-in vulnerabilities.

“Unless you’re really careful, a hacker can subtly manipulate inputs to these models to make them predict anything,” says Shashank Srikant, a graduate student in MIT’s Department of Electrical Engineering and Computer Science. “We’re trying to study and prevent that.”

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Opportunity to Publish AI Related Papers in a Peer-Reviewed Journal w/o cost. One in the BICA*AI 2021 Conference and the Philosophy and Computing Conference at IS4SI Summit in September.

One of the bigger problems I have run into in doing research out of a small lab is the cost of publishing papers and get them peer-reviewed. Many of the most specialized scientific conferences like BICA Society (Biologically Inspired Cognitive Architectures for AI) can not afford to subsidize costs. This means limits on how many papers can be released and spreading papers over many years sometimes. Recently I got invited to produce and help produce two scientific conferences at the IS4IS summit in September, and the best part is that IS4SI has gotten a grant to cover publishing costs. This means everyone for both conferences is able to publish (assuming your paper meets standards) and attend for free.

If for some reason, your paper does not meet the quality or topic bar’s, we can help you. So the two VIRTUAL conferences are:

BICA*AI 2021 – Biologically Inspired Cognitive Architectures for AI (I’m the chair on this one) This conference contributing to the 2021 Summit of the International Society for the Study of Information (IS4SI), is about how data and data architecture is used and implemented in theory and practice in agent-based systems using cognitive architectures that are inspired in large part by the human and animal mind. All aspects of information theory and information architecture in a Biologically Inspired Cognitive Architectures (BICA) based system may be covered. This conference is about information theory from the BICA perspective.

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