NXT Checkout Scanner

This Checkout Scanner project I posted recently uses the NXT 2.0 Color Sensor in Light Sensor mode to scan simple "barcodes" made out of LEGO beams and imitate a laser barcode scanner. The interesting thing is how fast it is able to work (the standard light sensor would be as fast as well). Here is a video of the scanner in action:

This project was inspired a bit by one of the missions on the FLL board this year, the Medicine Dispenser, where teams might want to use a light sensor to count black lines on the mat to get the exact distance right. My team was doing this mission and driving very slowly to make sure the sensor was able to count the lines properly. As I was watching them, I was thinking this was one of those cases where your instincts as a human don't relate well to what a robot can do. I knew the sensor could work much faster (and therefore the motor response is the limiting factor, not the sensor), but I was curious how much faster. So I did some tests and then thought of this project.

It turns out you can take light readings about 300 times per second, which is fast enough to do some pretty fast scanning. When you are working on data coming in this fast, it helps to visualize it in graph form, so also included in the programming instructions for this project are a program and some instructions on how to do some basic "data logging" on the NXT, to get sensor data from the sensor, transfer it to the PC, and graph it, as shown in this sample graph:

The data logging program and instructions are for doing it "manually", not using the built-in Data Logging feature of NXT-G 2.x from LEGO Education, which is not available in the retail software, and in any case is limited to only 25 samples per second, so it's not fast enough for this application.

MINDSTORMS Retires!

2023 is the 25th Anniversary of the MINDSTORMS brand. For 25 years, MINDSTORMS has educated and inspired a generation of robot builders, both children and adults. Unfortunately, the LEGO Group decided to end the line on December 2022. Many ROBOTMAK3RS have been passionately involved with the development of MINDSTORMS through the MUP and MCP programs. Even with the newest Robot Inventor line, several ROBOTMAK3RS were invited to submit additional bonus models that were included in the official app. Regardless of the retirement of a major LEGO robotics product line, ROBOTMAK3RS continue to MAKE-SHARE-INSPIRE using all LEGO robotics platforms available to us. Here is the official statement from LEGO. Since its launch in September 1998, LEGO MINDSTORMS has been one of the core ‘Build & Code’ experiences in the company’s portfolio, carrying with it significant brand equity and becoming a stand-out experience for the early days of consumer robotics and leading to current Build & Code

Celebrating 25 Years of MINDSTORMS

In celebration of the 25th Anniversary of MINDSTORMS, we take a trip through history. Please also visit ROBOTMAK3RS Community every week as we highlight different projects all through 2023 in celebration of the anniversary. Some of the early history is based on the content shared by Coder Shah in our MINDSTORMS EV3 Community Group . Some of the text and links may have been edited from his original posts for consistency and clarity. 1984 - Kjeld Kirk Kristiansen watched a TV program called "Talking Turtle," where MIT professor Seymour Papert demonstrated how children could control robot "turtles" using LOGO, a programming language he developed. 1988 - The collaboration between MIT and LEGO resulted in LEGO TC Logo in 1988, which allowed students to control LEGO models using computer commands. The video shows Papert demonstrating TC Logo. 1990 - LEGO TC Logo was hampered since the robots you built had to be tethered to a personal computer. LEGO and MIT

Celebrating MINDSTORMS with a Remix Part 1

In honor of the 25th Anniversary of MINDSTORMS, we asked ROBOTMAK3RS to combine a LEGO set of their choice with a MINDSTORMS set. Here is what these five ROBOTMAK3RS came up with. MINDSTORMS Chess Assistant by Arvind Seshan Overview: When you are new to chess, it can be a challenge to remember which pieces go where. Now, you can use machine learning and LEGO MINDSTORMS Robot Inventor to build a tool to help you learn where all the chess pieces go on the chess board. Sets used: LEGO® Iconic Chess Set (40174) and MINDSTORMS Robot Inventor (51515) Review: I really like how the chess set base can store all the pieces underneath and that the board neatly splits in half for handy storage. The chess pieces themselves are very sturdy and well built. My only criticism is the building of the box itself. It was quite difficult to see what pieces to use and since the entire box is made mostly of thin plates, it took a lot of time and patience. I would have liked the storage area to be sliding dra

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