If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
Study hard enough, kids, and maybe one day you'll grow up to be a professional robot fighter. A few years ago, Boston Dynamics set the standard for the field by having people wielding hockey sticks try to keep Spot the quadrupedal robot from opening a door. Previously, in 2015, the far-out federal research agency Darpa hosted a challenge in which it forced clumsy humanoid robots to embarrass themselves on an obstacle course way outside the machines' league. And now, behold: The makers of the Jueying robot dog have taught it a fascinating way to fend off a human antagonizer who kicks it over or pushes it with a stick. A team of researchers from China's Zhejiang University--where the Jueying's hardware was also developed--and the University of Edinburgh didn't teach the Jueying how to recover after an assault, so much as they let the robot figure it out.
Developing machine learning enabled smart manufacturing is promising for composite structures assembly process. To improve production quality and efficiency of the assembly process, accurate predictive analysis on dimensional deviations and residual stress of the composite structures is required. The novel composite structures assembly involves two challenges: (i) the highly nonlinear and anisotropic properties of composite materials; and (ii) inevitable uncertainty in the assembly process. To overcome those problems, we propose a neural network Gaussian process model considering input uncertainty for composite structures assembly. Deep architecture of our model allows us to approximate a complex process better, and consideration of input uncertainty enables robust modeling with complete incorporation of the process uncertainty. Based on simulation and case study, the NNGPIU can outperform other benchmark methods when the response function is nonsmooth and nonlinear. Although we use composite structure assembly as an example, the proposed methodology can be applicable to other engineering systems with intrinsic uncertainties.
TinyML is the latest from the world of deep learning and artificial intelligence. It brings the capability to run machine learning models in a ubiquitous microcontroller - the smallest electronic chip present almost everywhere. Microcontrollers are the brain for many devices that we use almost every day. From a TV remote controller to the elevator to the smart speaker, they are everywhere. Multiple sensors that can emit telemetry data are connected to a microcontroller.
Have a look at 2020's best robot vacuums -- all tried and tested in my office and home. A new project that forms a data visualization of brain signals in clothing has recently been showcased at the virtual Ars Electronica festival. The robotic dress is coupled to 1,024 channels of a BCI (Brain-Computer Interface) and has 64 outputs for light and movement. The Pangolin Scales' dress components function like animatronic elements that move and light up based on the recordings of the brain waves. The project originated at the Institute for integrated circuits at JKU (Johannes Kepler University, Linz, Austria), in collaboration with the Austrian Neurotechnology company G.tec.
If I were to picture futuristic bots that could revolutionize both microrobotics and medicine, a Pop-Tart with four squiggly legs would not be on top of my list. Last week, Drs. Marc Miskin*, Itai Cohen, and Paul McEuen at Cornell University spearheaded a collaboration that tackled one of the most pressing problems in microrobotics--getting those robots to move in a controllable manner. They graced us with an army of Pop-Tart-shaped microbots with seriously tricked-out actuators, or motors that allow a robot to move. In this case, the actuators make up the robot's legs. Each smaller than the width of a human hair, the bots have a blocky body equipped with solar cells and two pairs of platinum legs, which can be independently triggered to flex using precise laser zaps.
A MuJoCo wrapper provides convenient bindings to functions and data structures. The PyMJCF and Composer libraries enable procedural model manipulation and task authoring. The Control Suite is a fixed set of tasks with standardised structure, intended to serve as performance benchmarks. The Locomotion framework provides high-level abstractions and examples of locomotion tasks. A set of configurable manipulation tasks with a robot arm and snap-together bricks is also included.
Minimally invasive laparoscopic surgery, in which a surgeon uses tools and a tiny camera inserted into small incisions to perform operations, has made surgical procedures safer for both patients and doctors over the last half-century. Recently, surgical robots have started to appear in operating rooms to further assist surgeons by allowing them to manipulate multiple tools at once with greater precision, flexibility, and control than is possible with traditional techniques. However, these robotic systems are extremely large, often taking up an entire room, and their tools can be much larger than the delicate tissues and structures on which they operate. A collaboration between Wyss Associate Faculty member Robert Wood, Ph.D. and Robotics Engineer Hiroyuki Suzuki of Sony Corporation has brought surgical robotics down to the microscale by creating a new, origami-inspired miniature remote center of motion manipulator (the "mini-RCM"). The robot is the size of a tennis ball, weighs about as much as a penny, and successfully performed a difficult mock surgical task, as described in a recent issue of Nature Machine Intelligence. "The Wood lab's unique technical capabilities for making micro-robots have led to a number of impressive inventions over the last few years, and I was convinced that it also had the potential to make a breakthrough in the field of medical manipulators as well," said Suzuki, who began working with Wood on the mini-RCM in 2018 as part of a Harvard-Sony collaboration.
Semiconductors aren't the only silicon technology racing to outpace Moore's Law. Researchers from Cornell University unveiled an entire robot that is teensy enough to fit most anywhere in the human body -- yes, even in there -- and inexpensive enough to produce on a mass scale. The walking robots are the creation of Cornell physics professor Itai Cohen, professor of physical science Paul McEuen, and assistant professor at the University of Pennsylvania, Marc Miskin. This is not Cohen's first microscopic rodeo, mind you. This work builds off of his previous efforts on origami-inspired, shape-shifting, micro-machines and manages to overcome a significant hurdle that's been plaguing the field: the lack of a "micrometre-scale actuator system that seamlessly integrates with semiconductor processing and responds to standard electronic control signals," according to the team's study published Wednesday in Nature.
A troop of a million walking robots could enable scientific exploration at a microscopic level. Researchers have developed microscopic robots before, but they weren't able to move by themselves, says Marc Miskin at the University of Pennsylvania. That is partly because of a lack of micrometre-scale actuators – components required for movement, such as the bending of a robot's legs. Miskin and his colleagues overcame this by developing a new type of actuator made of an extremely thin layer of platinum. Each robot uses four of these tiny actuators as legs, connected to solar cells on its back that enable the legs to bend in response to laser light and propel their square metallic bodies forwards.
In 1959, Nobel laureate and nanotechnology visionary Richard Feynman suggested that it would be interesting to "swallow the surgeon" -- that is, to make a tiny robot that could travel through blood vessels to carry out surgery where needed. This iconic imagining of the future underscored modern hopes for the field of micrometre-scale robotics: to deploy autonomous devices in environments that their macroscopic counterparts cannot reach. However, the construction of such robots presents several challenges, including the obvious difficulty of how to assemble a microscopic locomotive device. In a paper in Nature, Miskin et al.1 report electrochemically driven devices that propel laser-controlled microrobots through a liquid, and which could be easily integrated with microelectronics components to construct fully autonomous microrobots. Designing propulsion strategies for microrobots that move through liquid environments is challenging because strong drag forces prevent microscale objects from maintaining momentum2.