"The startups that have made it to the final competition are indicative of the levels of innovation in the machine vision and imaging industries," according to Jeff Burnstein, President, AIA. "I don't envy the job in front of our judges having to select only one winner."
While the vision systems of old were unreliable, clunky and expensive, todays systems are anything but. Proper vision systems can make the difference between an efficient robotic system and one that is not working optimally.
Embedded vision solution with USB 3.0 board-level camera.
Siyi Chen for Quartz: A prototype created by the scientists can catalogue items instantly as the drones fly up and down the aisles.
The use of compact devices that run embedded software is becoming increasingly popular in industrial environments. From smart cameras and vision sensors to smart phones, tablets, and handheld devices, it is almost impossible to imagine connected and highly automated Industry 4.0 processes without these small devices.
Frame grabbers are no longer exclusively used in machine vision; they are today an essential component of dozens of industries. It is therefore important that the frame grabber manufacturer is involved in standards committees and other groups monitoring the evolution of this fast-changing technology.
Ashley Nickle for The Packer: SuperPick - short for supervisory picking - aims to provide the depth perception and recognition of 3-D using 2-D hardware and human oversight.
Xilinx Demonstrates Responsive and Reconfigurable Vision Guided Intelligent Systems at Embedded World 2017
Xilinx's tools, libraries and methodologies infuse machine learning, computer vision, sensor fusion, and connectivity into vision guided intelligent systems
Real-time video enhancement system offers plug and play solution for military ISR video
Vision 2016 Trend Report: From hyperspectral systems, embedded vision and 3D technology to machine vision technology in detail
Machine vision integrator collaborates with leading Swiss software firm
Enabling a full object view with just one camera.
Steve Arar for All About Circuits: Recently, Vijay Kumar’s lab at the University of Pennsylvania in cooperation with researchers from Qualcomm has unveiled a quadrotor which can fly aggressively through a window. You may think that you have seen similar robots before; however, there is a big difference between previously designed robots and this new technology. Generally, to exhibit challenging maneuvers, a quadrotor depends on an array of cameras mounted on the walls and some external processors. The image captured by the cameras is processed and the outcome is delivered to the robot. The computer can issue precise commands and the only thing that the robot needs to do is to follow the orders. However, the new robot performs both the image capturing and processing onboard. The quadrotor carries an IMU, a Qualcomm Snapdragon, and Hexagon DSP. With the onboard sensors and processors, the robot is able to perform localization, state estimation, and path planning autonomously. Cont'd...
Unlike pure Computer Vision research, Robot Vision must incorporate aspects of robotics into its techniques and algorithms, such as kinematics, reference frame calibration and the robot's ability to physically affect the environment.
BitFlow's BitBox™ Simplifies Integration and Control of Multiple Machine Vision Devices in High I/O Applications
Machine makers in high-density I/O vision applications are challenged daily to find cost-effective, reliable ways to continuously control dozens of devices such as strobes, solenoids, and actuators, as well as to acquire data input from equipment ranging from photo detectors to triggers. Until now, the answer has been to purchase an I/O card yet this step requires additional costs, software, system complexity, and the use of a PC slot.
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App Your Sensor®! What would smartphones be without apps? They would be mobile phones that can't do much more than make phone calls and sending SMS. Apps turn smartphones into intelligent assistants with any number of different tasks. Transferred into the world of image processing, this app-based approach transforms cameras and sensors into customised, smart vision sensors.