Slamtec’s RPLIDAR A2 Has a Range of 6 Meters And Can Take Up To 4000 Samples of Laser Ranging per Second ($480)

Slamtec China has announced the RPLIDAR A2 2D laser scanner which can take up to 4000 samples of laser ranging per second at a range of 6 meters. The RPLIDAR A2 features a LIDAR unit A2M4-R1 and an embedded motor controller to increase/decrease the speed of the motor or stop them.

This sensor is supposed to be used in robotics for autonomous navigation, localization, and obstacle avoidance. This means that you can use it indoor as well as outdoor. If the LIDAR technology embedded in the sensor has excellent performance when is used for indoor applications, for outdoor applications it should not be exposed to direct sunlight.

RPLIDAR A2 - 360 Degree Laser Scanner Development Kit

RPLIDAR A2 – 360 Degree Laser Scanner Development Kit


RPLDIAR-A2 Specifications

  • Distance Range: 0.15 – 6 m
  • Angular Range: 0-360 degree
  • Distance Resolution: <0.5 (0.15~1.5 meters)
    <1% of the distance (All distance range)
  • Angular Resolution: 0.9degree
  • Sample Duration: 0.25 millisecond
  • Sample Frequency 4000Hz
  • Scan Rate: 10Hz
  • Weight: 340g

The LIDAR kit comes with a USB adapter to connect the sensor to a PC. But if you’re looking to work with Arduino or any other development board, the RPLIDAR A2 is interfaced using the UART bus. Read more →

How I Hacked The mBot Ranger Kit For Autonomous Driving Capabilities

Two weeks ago, I wrote a review of the mBot Ranger kit. It was for the first time when I’ve been playing with a Makeblock kit, and I was impressed. Quality components, a lot of room for further extensions, etc. You can read more about my experience with the kit in the mBot Ranger review. In this post, I’ll continue my experience with the mBot Ranger, and I shared with you how I hacked the mBot Ranger kit to work autonomously using the ultrasonic sensor.

After 30 minutes of working, I assembled all the hardware components of the mBot kit into a nice robot tank. I was very happy, at least until I get into the software side. The kit can be programmed via PC or using an application. Very soon I found that I have some problems with the documentation, and the software version of the smartphone was not up to date because the kit hadn’t been released at that moment. Regarding the tablet version of the software, I don’t own a tablet. (Yes, I don’t want a tablet!)

Luckily, I knew that the brain of the robot is a Me Auriga brick based on Arduino Mega 2560. Being an Arduino fan, I know what to do to move forward.

The plan was to search in the libraries and find the pins to control the robot motors using the Arduino sketch. After a few minutes of research, I found the pins that I needed to control the two DC motors. Working with the ultrasonic sensor was much easier. I use the Makeblock library to read the distance from it. Read more →

$14.90 Towerpro MG938 Digital Servo Motor With Metal Gear and a Stall Torque of 3.7kg/cm At 6.1V

The Taiwanese company Towerpro released a new digital servo motor – MG938. The MG938 is part of the X-Large Servo 50g+ series and features a metal gear, a stall torque of 2.9kg/cm at 4.8V or 3.7kg/cm at 6.1V, and an operating voltage range between 4.8 and 6V. The price for one piece of MG938 is around $14.90 on the Towerpro website. If you want to buy four of them, the price is around $83.17 + $3.81 shipping on Amazon.
51Ev72y-1+L
MG938 Specifications

  • Weight: 31g
  • Dimension: 35.4*15.2*29.6mm
  • Stall torque: 2.9kg/cm(4.8v) ; 3.7kg/cm(6.1v)
  • Operating speed: 0.11sec/60degree(4.8v) ; 0.09sec/60degree(6.0v)
  • Operating voltage: 4.8-6.0V
  • Temperature range: 0- 55deg
  • Servo Plug: JR (Fits JR and Futaba)
  • Gear Type: Metal gear
  • Double Bearing
  • Dead band width: 1us
  • Power Supply: Through External Adapter
  • Servo wire length: 32cm
  • Servo Plug: JR (Fits JR and Futaba)

(image: Amazon)

Rally drivers are obsolete. This is a mini rally robot car that teaches itself to powerslide.

The rally car of the future is a robot that drives itself. The researchers from Georgia Tech uses an RC truck, ROS, and the NVIDIA graphics board to build a mini rally robot car that teaches itself to powerslide.

The code is open-source and ROS compatible. They use GitHub to host the source code and instructions. You can download the files from here.

Conclusion

  • The robots can learn to choose the better path.
  • The robot can drive aggressively and safe at the same time.
  • Rally drivers become obsolete.
  • Taking a seat in a self-driving sports car will not be boring anymore.

Robotpark Released a 4X4 Metal Body for Mobile Robots

The designing and building process of the metallic structure for an all-terrain robot is often harder and longer. Robotpark released a new 4×4 metallic platform body for wheeled mobile robots able to explore uneven terrains.

The platform comes with all the mechanical components. In that way solve all the problems associated with the mechanical structure.

Besides the ultrasonic sensor attached in front of the platform, the only thing that has to add are the electronics systems that control the robot.

Two big DC motors provide tractions to all four wheels. Each wheel has attached a suspension system for locomotion on uneven terrain, and differential steering systems for all four wheels.

All these features come at a price: $990.00 plus shipping.
95107_001-700x700
Here is a demo of the platform:

(Image credit: Robotpark)

An Autonomous Robot Connected to The Internet


If you’ve ever thought about getting into autonomous robots connected to the Internet, here’s a chance to learn how to build a robot rover with Internet over GPRS connection, GPS and distance sensors.

In this video, Jorge Crespo shares some features about the autonomous and manual mode of the robot. Here are some details:

  • Autonomous mode: in this mode, the robot uses the distance sensors to detect and avoid obstacles;
  • Manual mode: using an IoT application, the user sends specific commands to the robot;

The GPS module attached to the robot sends position data to the server so you can check the robot location and route on the map.

The brain of the robot is an Arduino Mega. The code and other resources are on GitHub.

Makeblock mBot Ranger Kit Review

IMG_0607
These days I got an mBot Ranger for free, and I want to say many thanks to Makeblock for this great kit. The normal price for this kit is around $149.99, but it hasn’t yet been released. If you want to play these days with an older version of mBot, you can find them on Amazon. Otherwise, you have to wait until 23rd May 2016 can buy the mBot Ranger kit.

Autonomous metal robots are hard to build from scratch unless you own a chassis kit and have degrees in electronics and programming. That’s what makes Makeblock’s mBot Ranger sets so amazing. The mBot Ranger kit combines sensors, motors, and an electronic brain with solid anodized aluminum parts, wheels, and tracks to make robots anyone can build. Of course, the robot can also be wirelessly controlled via Bluetooth connection. But I like more the autonomous way.

The good, the bad

The good

  • well designed with focus on details;
  • easy assembly;
  • strong and quality components;
  • a lot of room for further extensions;

The bad

  • if you want to change the batteries, you need to have with you the wrench included in the kit;
  • the documentation is not up to date;
  • I have some bad experience with the MeAuriga firmware. A lot of errors at installation in the Arduino IDE;

Read more →

Build Your Cheap Autonomous Robot By Following This Guide

F3ZG4SUIO09FQ0U.LARGE
The more intelligent you want to build a robot, the more complicated it seems that your project becomes. If you’re feeling overwhelmed but still want to build a cheap autonomous robot, take it one step at a time by following this guide about how to build an intelligent robot.

The Instructables user Imetomi shows us how to build on a cheap chassis a robot able to detect obstacles, explore the world with its FPV camera, react to sounds, hold and push objects and recharge its batteries with a solar panel.

The designer uses an Arduino clone to control the robot and a cheap 4WD platform which is priced around $25/kit.

For more information, you’ll want to check out the DIY intelligent autonomous robot’s post at the link below.

DIY Intelligent Autonomus Robot (Electronic Pet) /w Arduino | Instructables

(image credit: Instructables)

The Latest OpenCV Tutorials For Detecting and Tracking Objects

Computer vision applications aren’t only particular to experienced developers these days. The amateur DIYers are looking to develop with new and advanced algorithms in computer vision the next autonomous robot or security system. Considering all of these aspects, in this post I explore the latest OpenCV detection and tracking tutorials with applicability in robotics and automation.

A few months ago, I posted another article with a long list of OpenCV tutorials and examples.

  • Nobody Parks Here!
    Computer vision is an excellent way to check if somebody uses your parking spot. DIYer Ron Dagdag shows his cloud application which uses a Raspberry Pi as the brain, a cheap Web camera, and the OpenCV library.
    dont park here
  • Detecting Circles with OpenCV and Python
    Since its release, the OpenCV library has been hailed as the perfect all-in-one computer vision library. Now, it’s easier to detect and track objects in real-time. In this Instructables tutorial, the developer ShubhamIoT shows us how to detect circles in real-time. The computer vision application can be used for common scenarios.
    002
  • Determining object color with OpenCV
    Adrian Rosebrock helps you understand how to determine the shape detection and color labeling in images using Python and OpenCV.
    This computer vision application is useful in semi-controlled lighting conditions and only for small color sets.
    determining_object_color_result
  • Saving key event video clips with OpenCV
    Do you need a computer vision application to detect key events? If yes, the same guru – Adrian Rosebrock – in OpenCV and computer vision applications explains how to build from scratch an application that saves key event video clips.

    This application is useful if you want to detect motion in a restricted access zone or an intruder in your house.
    key_event_demo

  • Messenger Basketball Playing Robot
    If you’re an Arduino user, DIY-er, game builder, or just like to use computer vision for fun, you need to see this application. In this application, the OpenCV library is used to play a basketball game on a smartphone. The robot is a 3 degree-of-freedom arm that uses a stick to interact with the screen of the smartphone.
    finished
  • Measuring size of objects in an image with OpenCV
    One of the things you’re probably thinking of when looking at a photo with different objects is the size of the objects. The OpenCv library is again the best way to measure the size of objects reported at a reference object in an image.
    size_of_objects_example_02
  • Finding extreme points in contours with OpenCV
    In a tutorial on his blog, Adrian Rosebrock shows us how to find the extreme points in contours with OpenCV. This tutorial is useful for a more advanced hand gesture recognition application.
    extreme_points_header
  • Automatic Face Detection in Photos with PHP
    If you’re wondering how to detect faces with OpenCV and PHP script, this is the tutorial where you find how to use the PHP facedetect extension with the OpenCV library.
    fresult

(image credit: hackster, instructables, pyimagesearch, github, corpocrat)

An Autonomous Robot Able To Inspect a Building, Create a Map of It, and Locate Objects On the Map


Building an autonomous indoor robot able to inspect a building, create a map of it and locate objects on the map is not a handy task since it requires knowledge, time and budget.

This indoor mobile robot aims to make the autonomous navigation easier by integrating a set of sensors with artificial intelligence algorithms.

The sensors attached to the mobile platform are:

  • Sick LMS100 Lidar (a sensor with sensing range of 18 meters and an error of about 20mm)
  • KHV Gyrocompass
  • RGB-D Depth Camera (Kinect-like)

The idea here is to combine hardware resources with many artificial intelligence algorithms to increase the autonomy of the robot. In this case, the autonomous exploration, finding the optimal path, Simultaneous Localization and Mapping (SLAM), automatic path following, obstacle detection and avoidance, and a real-time path re-planning.

All of these features make the robot available for teleoperation, mission planning on maps, real-time mission follower, or robot state and alerts display.

It’s not a simple autonomous robot, but you can find out some inspiration to build a replica of it for yourself over on Robopec’s page.