MotionCam-3D by Photoneo enables 3D scanning & handling of objects that are moving on an overhead conveyor without interruption. The camera provides high-quality 3D data even while the objects are moving, swinging, or slightly rotating.
MotionCam-3D by Photoneo enables 3D scanning & handling of objects that are moving on an overhead conveyor without interruption. The camera provides high-quality 3D data even while the objects are moving, swinging, or slightly rotating.
ETH researchers led by Marco Hutter developed a new control approach that enables a legged robot, called ANYmal, to move quickly and robustly over difficult terrain. Thanks to machine learning, the robot can combine its visual perception of the environment with its sense of touch for the first time.
This article explores TPU vs GPU differences in architecture, performance, energy efficiency, cost, and practical implementation, helping engineers and designers choose the right accelerator for AI workloads today!
EPFL roboticists have shown that when a modular robot shares power, sensing, and communication resources among its individual units, it is significantly more resistant to failure than traditional robotic systems, where the breakdown of one element often means a loss of functionality.
MIT researchers' DiffSyn model offers recipes for synthesizing new materials, enabling faster experimentation and a shorter journey from hypothesis to use.
MotionCam-3D by Photoneo enables 3D scanning & handling of objects that are moving on an overhead conveyor without interruption. The camera provides high-quality 3D data even while the objects are moving, swinging, or slightly rotating.
ETH researchers led by Marco Hutter developed a new control approach that enables a legged robot, called ANYmal, to move quickly and robustly over difficult terrain. Thanks to machine learning, the robot can combine its visual perception of the environment with its sense of touch for the first time.
In this article, we take a look at two tinyML projects related to healthcare. The first project helps gather Mean Radiant Temperature data outdoors to protect people from extreme heat, and the other one is a solution for affordable, accurate, & rapid detection of pneumonia.
Removing litter from oceans and seas is a costly and time-consuming process. As part of a European cooperative project, a team at the Technical University of Munich (TUM) is developing a robotic system that uses machine learning methods to locate and collect waste under water.
Ultra-precise lasers can be used for optical atomic clocks, quantum computers, power cable monitoring, and much more. But all lasers make noise, which researchers from DTU Fotonik want to minimize using machine learning.
In this episode, we talk about how a breakthrough with compact laser nano-printers can make them more accessible for researchers and how leveraging 3D printing technology and machine learning will provide essential insight for developing next-gen cochlear implants.
In this article, we take a look at two tinyML projects that have the potential to make contributions towards sustainable development goals. While the first project is about revolutionising precision farming, the second one aims to create a network of low-cost sensors for mapping carbon emissions.
Edge Impulse recently announced official support for the Syntiant NDP101 processor, an always-on sensor and speech recognition processor, with ultra-low power consumption of less than 140 uW while recognizing words.
KOPR spol. s.r.o. developed a solution for advanced laser cutting of heavy hot-formed parts and their subsequent quality check. The solution deploys 3D vision and Bin Picking Studio from Photoneo and an ABB robot.
In this episode, we talk about how computer vision works and discuss an application coming out of the Technical University of Denmark that can help dairy farmers remove weeds from their fields.