Engineering-first robotics, AI, maker hardware, STEM, and creator technology reporting
Robotics and AI covers physical AI, industrial automation, robots, machine vision, edge AI hardware, simulation, safety, and deployment workflows, emphasizing what technical teams should evaluate before adoption.
A review-preview buyer evaluation of Yahboom’s ROSMASTER X3 Plus robotics platform, focused on setup repeatability, calibration, ROS lessons, power stability, and classroom durability.
Yahboom ROSMASTER X3 Plus Review Preview: A ROS Robot Worth Testing Read More
Global shutter and rolling shutter cameras can both work in robot projects, but motion, lighting, calibration and cost decide which one belongs on the robot.
Global Shutter vs. Rolling Shutter Is a Robot Vision Reliability Choice Read More
Google DeepMind says Gemini Robotics 2 can control humanoids and bi-arm robots from feet to fingertips. The useful question is how that progress survives real robot variation, safety constraints and repeatable evaluation.
Gemini Robotics 2 Pushes Google DeepMind Further Into Whole-Body Robot Control Read More
Before rewriting AprilTag code, check print size, border quality, glare, distance, camera calibration, and lighting. Many robot demo failures start on paper.
AprilTag Print Size and Glare Can Break a Robot Demo Before the Code Does Read More
Before blaming the model, test the lighting. Robot vision projects need exposure, glare, shadows, calibration targets, frame rate, and field logs in the checklist.
Robot Camera Lighting Should Be Tested Before You Blame the Model Read More
Raspberry Pi AI projects can make local inference tangible for students, but classrooms need a validation checklist for cameras, data, latency, privacy, and failure logs.
Raspberry Pi AI Projects Need a Classroom Validation Checklist Read More
Raspberry Pi AI projects can fail for storage reasons. This TVG buyer guide explains when a microSD card is enough and when a USB SSD belongs in the classroom kit.
MicroSD Card or USB SSD for Raspberry Pi AI Projects? Read More
AprilTags can make classroom robot vision feel reliable, but small layout mistakes can break a demo. Use a repeatable checklist for placement, lighting, calibration, and logs.
AprilTag Layout Mistakes Can Break a Classroom Robot Vision Demo Read More
Camera calibration is not a one-time setup step. Classroom and lab robots need repeatable checks for mounts, focus, lighting, timestamps, and field targets before vision data can be trusted.
Robot Camera Calibration Should Be a Checklist, Not a One-Time Setup Read More
More images do not automatically make an AI camera project better. Builders need label rules, negative examples, lighting variation, and field checks.
Raspberry Pi AI Camera Projects Need a Labeling Plan Before More Images Read More