Yearly Archives: 2016

RGB LED Strip Controller for LEGO Mindstorms EV3 or NXT

EV3Lights
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Some may have seen my article, “Using WS2812B Addressable RGB LED Strips with Arduinos“, back in September? As can be seen in that article, controlling Addressable LEDs is pretty straight forward with a basic knowledge of the I2C protocol. I had planned to cobble together interface to allow RGB LED Strip to be Controller by either a LEGO Mindstorms NXT or EV3 Brick, but my teaching commitments and over projects seemed to have forced the idea onto the back-burner. Thanks to Mindsensor, I have no need to warm up the soldering for the idea as they have come up with a ready assembled interface.

Start Up & Run a Robotics Team

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Have you thought about starting a robotics team or do your run one already but want to learn more. Let us show you how. Whether you wish to start a primary or secondary school team, or even an independent team like ourselves, we can guide you through the minefield of what you need to know and do.

fllprogramminglessons

The day will cover:

  • What is FLL and FTC ?
  • The Robots (EV3 and Android).
  • Programming/building/design
  • The FLL and FTC Competitions.
  • Costs of running a team, what to buy, ongoing costs.


Places are limited and booking is essential. Please bring along your own lunch and drinks.

Metal Minds Robotics Inc. – Contact 0415866058

LEGO Mindstorms EV3 Ball Chasing Robot using the PixyCAM

PixyCAM Follow the Ball
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This article aims to describe how to programme a LEGO Mindstorms EV3 robot that chases things, like a ball in this example. It’s the same robot and program that’s used in the PixyCAM Video below. This robot and program is a good launching point for other projects, and it’s a good introduction to PID control, which is used throughout robotics and engineering in general.

Guide to using the PixyCAM Camera’s EV3-G Blocks

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In this article, I attempt to describe the LEGO PixyCAM block, which is used in conjunction with the LEGO Mindstorms EV3 Software. Check out the “Getting Started with the LEGO Mindstorms & the PixyCAM” Article for information on how to install the PixyCAM modules (Blocks) into Mindstorms EV3-G Software.

Getting Started with the LEGO Mindstorms & the PixyCAM

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I trust this article will get you up an running quickly with PixyCAM and the LEGO Mindstorms EV3 (NXT). Please make sure you have a LEGO Mindstorms EV3 or NXT brick with a fresh set of batteries. I will endeavor to be as detailed as possible throughout this guide, but it helps if you are somewhat familiar on how to use your LEGO Mindstorms Robotics System.

Connecting the PixyCAM to LEGO Mindstorms using I2C

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In order to use the PixyCAM with the LEGO Mindstorms EV3 or NXT kit, you will need an I2C Adapter Cable. You can order a cable through some PixyCAM distributors, including the Robotshop. The PixyCAM for LEGO Mindstorms comes with a special Pixy-to-Mindstorms Cable, and is preloaded with a version of the firmware that speaks with the LEGO protocol by default. If you have Pixy for LEGO, just to the PixyMon Settings section below.

Updating the PixyCAM’s Firmware

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When it comes to upgrading your PixyCAM to the latest Firmware is idiot proof. The PixyCam uses a ROM-based algorithm to upload new firmware into flash memory over USB, which makes Pixy “unbrickable” – that is, you will always be able to recover the PixyCAM from an unsuccessful firmware upload or a “bad” version of firmware.

Installing PixyMon on Linux

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1. Introduction

The following procedure will walk you through building PixyMon for Linux. This procedure assumes the following:

  • Your system has Linux (Mint-17) installed
  • Pixy firmware has been updated to 1.0.2
  • Your system is connected to the internet

The Mint-17 distribution of Linux can be downloaded here: http://www.linuxmint.com

‘Metal Minds Robotics’ FLL Team are Winners & Grinners !

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Thank you to the ‘Metal Minds Robotics’ team for a great FIRST LEGO League (FLL) Competition at the Tasmanian State Championships on Saturday 19 October 2016, held in Hobart. I trust everyone else enjoyed the day at least half as much as I did. It was fantastic to see our future Scientists, Technologists, Engineers, and Mathematicians putting their combined skills together for such a great out come.

Teaching the PixyCAM Camera an Object

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Teaching PixyCAM an object is super easy. Before we start, which objects will work well with PPixyCAM, and which wont? PixyCAM uses a hue-based colour filtering algorithm to detect objects. Since PixyCAM uses hue (colour), the object needs to have a distinct hue. Here are some objects that are good because they have good, distinct hues.

Installing PixyMon for the CMUcam5 Pixy Camera on a Windows PC

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I have finally gotten around to purchasing a CMUcam5 PixyCam for myself. The (CMUcam5) PixyCam is a Smart Vision Sensor, with advanced Object Tracking. One advantage of this Camera is that you can quickly “teach” it to locate objects. It saves you time and data flow by only outputting the object data that you’re interested in. A multitude of connection options are available which means you can use PixyCam with almost any microcontroller, including Arduinos, Raspberry Pi, BeagleBone Black and a dedicated LEGO Mindstorms version. I settled for the dedicated LEGO Mindstorms version of the PixyCam which plugs directly into a LEGO Mindstorms NXT or EV3 Sensor Port.

FLL Robot from a single EV3 31313 Kit: Mark II

FLL Robot from a EV3 Kit
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This is my second attempt at a FIRST LEGO League (FLL) Robot which can be made from a single LEGO Mindstorms EV3 (Home 31313) kit. It was built with the intention of being demonstration Robot that the team members of the Metal Minds Robotics Team I mentor could build at home with their own EV3 Kits.

Dual Container Grab Mechanism for STS Crane

dual container grab mechanism
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Over the last 8 months I have been working on Ship-to-Shore (STS) Bulk Container Handling Crane which is scaled to the LEGO 20′ Container that comes with LEGO Maersk  Train set. This Dual Container Grab Mechanism will hand two 40′ Containers, or four 20′ Container, or one 40′ & two 20′ Containers.

PID Control Theory Explained

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Overview

Proportional-Integral-Derivative (PID) control is the most common control algorithm used in industry and has been universally accepted in industrial control. The popularity of PID controllers can be attributed partly to their robust performance in a wide range of operating conditions and partly to their functional simplicity, which allows engineers to operate them in a simple, straightforward manner. 

Using the ‘Google Cloud Vision API’ with your Raspberry Pi

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What is the ‘Google Cloud Vision API’?

Google Cloud Vision API enables your robot to understand the content of an image by encapsulating powerful machine learning models in an easy to use REST API. It quickly classifies images into thousands of categories such as “robot”, “elephant”, “flower”. It detects individual objects and faces within images. It capable of finding and reading printed words contained within images, and even determines the language it is written in. You can use it to build metadata for your image collection, and can be used to moderate offensive content through image analysis.
The Vision API enables you to detect different types of inappropriate content from adult to violent content. It analyzes images uploaded by the request, or integrate with your image storage on Google Cloud Storage.



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