Non-Factory

Courtesy of John Deere
Figure 1: Viewing this problem as an opportunity, innovators have developed automated approaches to weeding—such as the machine pictured here from John Deere—that use machine vision, such as 3D imaging, and deep learning.
John Deere and other companies use embedded vision technology to distinguish between weeds and crops automatically, improving efficiency on commercial farms.
Aug. 13, 2025
All images/Advanced Navigation
Figure 1: Three Hydrus drones descending to the sea floor at Hall Bank coral reef, off the coast of Western Australia.
July 3, 2025
All images/figures courtesy of Edmund Optics
Fig. 1. System Throughput
June 2, 2025
Courtesy of Automation Intelligence
automation_intelligence_logo_fov_third_story
May 19, 2025
ID 356933713 | Machine © Vladimir Zlotnik | Dreamstime.com
Figure 1: Distribution yards have been pain points in the supply chain, in many cases because of delays in the movement of freight in and out of the yard. However, recent innovations using AI-assisted solutions may be the key to loosening up the bottleneck.
April 14, 2025
Courtesy of Carbon Robotics
Figure 1: Carbon Robotics markets an autonomy kit—including machine vision components and deep learning algorithms—as well as a self-contained system to kill weeds using lasers.
April 9, 2025
ID 203157943 | Machine © Phuttaphat Tipsana | Dreamstime.com
Figure 1: Stereo vision is often used in vision guided robotics in warehouses.
March 31, 2025
Courtesy of John Deere
Figure 1: The Autonomous 9RX Tractor for Large-Scale Agriculture uses cameras in pods with overlapping FOV.
Jan. 15, 2025
Courtesy of Edmund Optics
Figure 1: Microscope Objectives are responsible for gathering light from an object and forming an intermediate image, which is then either projected onto a sensor or magnified further by an eyepiece.
Dec. 16, 2024

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