Unveiling intra-person fingerprint similarity via deep contrastive learning.

Fingerprint biometrics are integral to digital authentication and forensic science. However, they are based on the unproven assumption that no two fingerprints, even from different fingers of the same person, are alike. This renders them useless in scenarios where the presented fingerprints are from different fingers than those on record.

Inverted laser sintering of metal powders.

We demonstrate the ability of the inverted laser sintering process to manufacture parts composed of metal powder. We fabricate a 10-layer part by depositing a layer of copper powder onto a sapphire plate, then pressing the plate against the part being built and sintering the powder onto the part by shining a 14W 445 nm laser through the glass. The process was then repeated multiple times, each time adding a new layer to the component being printed until completion.

Design and fabrication of carbon fiber lattices using 3D weaving.

We present a method of designing and fabricating 3D carbon fiber lattices. The lattice design and fabrication is based on crocheting and sewing techniques, where carbon fiber tow is woven through two parallel carbon fiber grids and reinforced with vertical carbon fiber tubes. Compression testing is then performed on three different designs, and these results are compared to other similar lattice structures, finding that the lattices perform similarly to comparable lattices.

Regenerative Topology Optimization of Fine Lattice Structures.

We present a generative approach for creating three-dimensional lattice structures optimized for mass and deflection composed of thousands of one-dimensional strut primitives. Our approach draws inspiration from topology optimization principles. The proposed method iteratively determines unnecessary lattice struts through stress analysis, erodes those struts, and then randomly generates new struts across the entire structure.

The future of software-controlled cooking.

To date, analog methods of cooking such as by grills, cooktops, stoves and microwaves have remained the world's predominant cooking modalities. With the continual evolution of digital technologies, however, laser cooking and 3D food printing may present nutritious, convenient and cost-effective cooking opportunities. Food printing is an application of additive manufacturing that utilizes user-generated models to construct 3D shapes from edible food inks and laser cooking uses high-energy targeted light for high-resolution tailored heating.

Electro-Osmotic Gripper Characterization for Layered Assembly.

Layered assembly is a voxel-based additive manufacturing process that relies on parallel grasping of voxels to produce multi-material parts. Although there exists substantial diversity in mechanisms of gripping, there still exists a lack of consistency, accuracy, and efficacy in positioning very large numbers of milli-, micro-, and nano-scale objects. We demonstrate the use of parallel electro-osmotic grippers to selectively transport multiple millimeter-sized voxels simultaneously.

What we look for at .

Science Robotics welcomes papers demonstrating technical and scientific advances, with potential for influence beyond robotics.

Fully body visual self-modeling of robot morphologies.

Internal computational models of physical bodies are fundamental to the ability of robots and animals alike to plan and control their actions. These "self-models" allow robots to consider outcomes of multiple possible future actions without trying them out in physical reality. Recent progress in fully data-driven self-modeling has enabled machines to learn their own forward kinematics directly from task-agnostic interaction data.

Automated discovery of fundamental variables hidden in experimental data.

All physical laws are described as mathematical relationships between state variables. These variables give a complete and non-redundant description of the relevant system. However, despite the prevalence of computing power and artificial intelligence, the process of identifying the hidden state variables themselves has resisted automation.

PARA: A one-meter reach, two-kg payload, three-DoF open source robotic arm with customizable end effector.

This article presents a robotic arm that is more cost effective than existing models on the market while still maintaining sufficient torque and speed capabilities. Most industrial-grade high power and precision arms are often very expensive, while conversely, more low-cost arms targeted toward the education and hobby sectors are inadequate in power and robustness. The Creative Machines Lab's three degree of freedom Printed Articulated Robotic Arm (PARA) can lift a 2 kg payload at a reach of 940 mm, while under a no-load case, it has exhibited a precision of about ±2.

Visual design intuition: predicting dynamic properties of beams from raw cross-section images.

In this work we aim to mimic the human ability to acquire the intuition to estimate the performance of a design from visual inspection and experience alone. We study the ability of convolutional neural networks to predict static and dynamic properties of cantilever beams directly from their raw cross-section images. Using pixels as the only input, the resulting models learn to predict beam properties such as volume maximum deflection and eigenfrequencies with 4.

Precision cooking for printed foods via multiwavelength lasers.

Additive manufacturing of food is a method of creating three-dimensional edible products layer-by-layer. While food printers have been in use since 2007, commercial cooking appliances to simultaneously cook and print food layers do not yet exist. A key challenge has been the spatially controlled delivery of cooking energy.

Visual behavior modelling for robotic theory of mind.

Behavior modeling is an essential cognitive ability that underlies many aspects of human and animal social behavior (Watson in Psychol Rev 20:158, 1913), and an ability we would like to endow robots. Most studies of machine behavior modelling, however, rely on symbolic or selected parametric sensory inputs and built-in knowledge relevant to a given task. Here, we propose that an observer can model the behavior of an actor through visual processing alone, without any prior symbolic information and assumptions about relevant inputs.

Layered assemblers for scalable parallel integration.

Many complex natural and artificial systems are composed of large numbers of elementary building blocks, such as organisms made of many biological cells or processors made of many electronic transistors. This modular substrate is essential to the evolution of biological and technological complexity, but has been difficult to replicate for mechanical systems. This study seeks to answer if layered assembly can engender exponential gains in the speed and efficacy of block or cell-based manufacturing processes.

Facially expressive humanoid robotic face.

Realistic humanoid robots have emerged in the last two decades but the emotional intelligence of these machines has been limited. To teach humanoids how to emotionally communicate with humans, researchers have been increasingly relying on machine learning algorithms. While the software used to implement machine learning algorithms is largely open source, facially expressive humanoid robots are expensive and inaccessible to most people, thus limiting the number of researchers in this field.

The Surprising Creativity of Digital Evolution: A Collection of Anecdotes from the Evolutionary Computation and Artificial Life Research Communities.

Evolution provides a creative fount of complex and subtle adaptations that often surprise the scientists who discover them. However, the creativity of evolution is not limited to the natural world: Artificial organisms evolving in computational environments have also elicited surprise and wonder from the researchers studying them. The process of evolution is an process that transcends the substrate in which it occurs.

Millimeter-Level Plant Disease Detection From Aerial Photographs Deep Learning and Crowdsourced Data.

Computer vision models that can recognize plant diseases in the field would be valuable tools for disease management and resistance breeding. Generating enough data to train these models is difficult, however, since only trained experts can accurately identify symptoms. In this study, we describe and implement a two-step method for generating a large amount of high-quality training data with minimal expert input.

Autonomous drone hunter operating by deep learning and all-onboard computations in GPS-denied environments.

This paper proposes a UAV platform that autonomously detects, hunts, and takes down other small UAVs in GPS-denied environments. The platform detects, tracks, and follows another drone within its sensor range using a pre-trained machine learning model. We collect and generate a 58,647-image dataset and use it to train a Tiny YOLO detection algorithm.

Selective laser broiling of Atlantic salmon.

Selective laser broiling is a novel food processing technique that utilizes a 2-axis mirror galvanometer system to direct laser power to cook raw food. Unlike conventional cooking processes, laser cooking benefits from the high spatial and temporal precision of power delivery. In this investigation, we use a trochoidal scanning pattern to optimize the cooking of Atlantic salmon (Salmo salar), which is used as a model food system.

Particle robotics based on statistical mechanics of loosely coupled components.

Biological organisms achieve robust high-level behaviours by combining and coordinating stochastic low-level components. By contrast, most current robotic systems comprise either monolithic mechanisms or modular units with coordinated motions. Such robots require explicit control of individual components to perform specific functions, and the failure of one component typically renders the entire robot inoperable.

Task-agnostic self-modeling machines.

A robot modeled itself without prior knowledge of physics or its shape and used the self-model to perform tasks and detect self-damage.

3D Printing and Heart Failure: The Present and the Future.

Advanced imaging modalities provide essential anatomic and spatial information in patients with complex heart disease. Two-dimensional imaging can be limited in the extent to which true 3-dimensional (3D) relationships are represented. The application of 3D printing technology has increased the creation of physical models that overcomes the limitations of a 2D screen.