Lifeboat Foundation

Existing electronic skin (e-skin) sensing platforms are equipped to monitor physical parameters using power from batteries or near-field communication. For e-skins to be applied in the next generation of robotics and medical devices, they must operate wirelessly and be self-powered. However, despite recent efforts to harvest energy from the human body, self-powered e-skin with the ability to perform biosensing with Bluetooth communication are limited because of the lack of a continuous energy source and limited power efficiency. Here, we report a flexible and fully perspiration-powered integrated electronic skin (PPES) for multiplexed metabolic sensing in situ. The battery-free e-skin contains multimodal sensors and highly efficient lactate biofuel cells that use a unique integration of zero- to three-dimensional nanomaterials to achieve high power intensity and long-term stability. The PPES delivered a record-breaking power density of 3.5 milliwatt·centimeter⁻² for biofuel cells in untreated human body fluids (human sweat) and displayed a very stable performance during a 60-hour continuous operation. It selectively monitored key metabolic analytes (e.g., urea, NH₄⁺, glucose, and pH) and the skin temperature during prolonged physical activities and wirelessly transmitted the data to the user interface using Bluetooth. The PPES was also able to monitor muscle contraction and work as a human-machine interface for human-prosthesis walking.

Recent advances in robotics have enabled soft electronic devices at different scales with excellent biocompatibility and mechanical properties; these advances have rendered novel robotic functionalities suitable for various medical applications, such as diagnosis and drug delivery, soft surgery tools, human-machine interaction (HMI), wearable computing, health monitoring, assistive robotics, and prosthesis (1–6). Electronic skin (e-skin) can have similar characteristics to human skin, such as mechanical durability and stretchability and the ability to measure various sensations such as temperature and pressure (7–11). Moreover, e-skin can be augmented with capabilities beyond those of the normal human skin by incorporating advanced bioelectronics materials and devices.

Researchers at Bilkent University in Turkey have recently created a small quadruped robot called SQuad, which is made of soft structural materials. This unique robot, presented in a paper published in IEEE Robotics and Automation Letters, is more flexible than existing miniature robots and is thus better at climbing or circumventing obstacles in its surroundings.

“We have been working on miniature robots for almost a decade now,” Onur Ozcan, one of the researchers who carried out the study, told TechXplore. “Even though miniature robots have many advantages, such as being cheap, as they require fewer materials, and the ability to access confined spaces, one of their major drawbacks is their lack of locomotion capabilities, especially on uneven terrain.”

Tiny robots tend to get stuck easily while moving in the surrounding environment, as their height does not allow them to climb or avoid obstacles. Ozcan and his colleagues tried to overcome this limitation by implementing a principle known as ‘body compliance.”

Nvidia CEO to unveil new tech on YouTube, and more from machine-learning world.

The main idea of artificial neural networks (ANN) is to build up representations for complicated functions using compositions of relatively simple functions called layers.

A deep neural network is one that has many layers, or many functions composed together.

Although layers are typically simple functions(e.g. relu(Wx + b)) in general they could be any differentiable functions.

In this article, I will demonstrate the use of Variational Inference to quantify the uncertainty in the weights of deep neural networks and make more informed predictions for a breast cancer classification dataset.

KIA and corporate cousin Hyundai build some efficient EVs that challenge industry leaders like Tesla. Yes, Elon an his minions are miles ahead in self-driving tech, but the Hyundai Kona EV and KIA Niro EV are world class cars that come close to meeting Elon’s plea to other manufacturers to build compelling electric cars.

The problem is, KIA and Hyundai don’t have a dedicated battery electric platform. Both the Kona and Niro share their underpinnings with hybrid and plug-in hybrid models. A pure battery electric car may be coming soon from KIA, however. Recently, Hyundai said it is planning to bring two new all electric models — the 45 Concept and the Prophesy Concept — to market this year and next. Both will be built on the company’s new Electric Global Modular Platform known internally as E-GMP.

Tesla’s progress with artificial intelligence and neural nets has propelled its Autopilot and Full Self Driving solutions to the front of the pack. This is the result of the brilliant work of a large team of Autopilot directors and staff, including Tesla’s Senior Director of AI, Andrej Karpathy. Karpathy presented Tesla’s methods for training its AI at the Scaled ML Conference in February. Along the way, he shared specific insights into Tesla’s methods for achieving the accuracy of traditional laser-based lidar with just a handful of cameras.

The secret sauce in Tesla’s ever-evolving solution is not the cameras themselves, but rather the advanced processing and neural nets they have built to make sense of the wide range and quality of inputs. One new technique Tesla’s AI team has built is called pseudo-lidar. It blends the lines between traditional computer vision and the powerful point map world of lidar.

Traditional lidar-based systems rely on an array of lidar hardware to provide an unparalleled view of the world around the vehicle. These systems leverage invisible lasers or similar tech to send a massive number of pings out into the world to detect surrounding objects.

Robots could soon assist humans in a variety of fields, including in manufacturing and industrial settings. A robotic system that can automatically assemble customized products may be particularly desirable for manufacturers, as it could significantly decrease the time and effort necessary to produce a variety of products.

To work most effectively, such a robot should integrate an assembly planner, a component that plans the sequence of movements and actions that a robot should perform to manufacture a specific product. Developing an assembly planner that can rapidly plan the sequences of movements necessary to produce different customized products, however, has so far proved to be highly challenging.

Continue reading “An algorithm to enhance the robotic assembly of customized products” »

Google announced in late 2010 that for the past year, Californian drivers had been sharing the road with a secret self-driving car project. Many years and one death at the hands of rival Uber later, we can finally see 2009’s testing footage.