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Autonomous Robot

53,100.00

ROS Robot is an autonomous robot, which has feature of reaching the Marked destination using Robotic Operating System (ROS) with Matlab

Features:

SLAM – Simultaneous Localisation and Mapping | Path Planning | Path Following

Shipping: 4 to 8 working days from the date of purchase

Package Includes:

  • Complete Hardware Kit

  • Demo Video-Embedded Below

  • Abstract

  • Reference Paper

  • PPT (20 Slides)

  • !!! Online Support !!!

10 in stock

SKU: Autonomous Robot Categories: ,

Description

Introduction

Everyone knows about the Turtlebot, the one popular bot which has indoor features like servicing. From the idea of turtle bot, this Autonomous Robot also uses SLAM algorithm for localization and Mapping, Path planning and Path following with only difference by using Matlab.


Short about ROS

ROS is the Robot Operating System, which is the software libraries use for developing the Robotic applications which also has some algorithms with some development tools. ROS is open source which is compatible in every Operating system and also by using Robotic Operating System Software package available in Matlab, we can access the Autonomous Robot from the Matlab.

There are a lot of versions of ROS. Like ordered alphabetically.

  • Hydro
  • Indigo
  • Jade
  • Kinetic

Tools of ROS like

  • Rviz
  • rosbag
  • catkin
  • rosbash
  • roslaunch

Short about SLAM

SLAM is Simultaneous Localisation and Mapping. It is used to map the unknown environment by tracking the current location of the Bot in that same environment. By using SLAM algorithm complete indoor servicing can be done by using Mapping with path planning and following.


Short about Lidar

LIDAR is Light Detection and Ranging uses Light in the form of a pulsed laser to detect the obstacle with its ranges. And by having continuous obtaining of ranges throughout the environment with precise angle difference between every ranges it is possible to map the whole environment which is known as Laser scans, which includes Ranges, Angles, Cartesian coordinates and Number of the value obtained. Based on Physical and Scattering process and platform LIDAR has many classifications.

Among those 360 degrees, lidar can be used for major applications.


Abstract

This is one of the Low-cost Autonomous Robot, which has simple structure uses ROS (Robotic Operating System) software library of version ROS Kinetic booted with Raspberry Pi and also interfaced with RPLidar in the front top portion of the Bot. This low-cost turtle bot emerges with features like SLAM (Simultaneous Localization and Mapping), Path planning and Path Following. which has the capability to reach the destination automatically after its destination is fixed in the Map. For those Applications, we are using Matlab’s Robotic Operating System Software package to communicate with ROS in the Raspberry Pi using ROS Network Configurations.


Existing system

In the existing robots, High-cost sensors and interfaces are used like Kinect camera and controllers or Laptops merged with RPlidar which makes it as expensive Bot than others.


Proposed system

In this proposed system new way of the method to reduce the cost, we used every basic model of hardware like Raspberry Pi as the core of ROS and using Rplidar A1 model which also a 360-degree functional lidar. For Robot control we are simply using Arduino interfaced with HC-05 Bluetooth to receive commands from the laptop. And rest of the functionalities like Algorithms like SLAM, Destination Marking, Path Planning and Path following are developed in Matlab using Robotic Operating System in Software Package of the Matlab. By using ROS Network configurations ROS is communicated from the Matlab.


Demo video


Block Diagram

Block diagram of ROS Robot


Block Diagram Description

  • Raspberry Pi is booted with Linux based OS with ROS Software Package
  • RPLidar A1  360 degree Lidar, interfaced with Raspberry Pi USB port
  • Robo chassis which contains the motor is interfaced with the Arduino through Motor Driver L293D
  • Also, HC-05 Bluetooth is connected with the Arduino
  • 9V battery is connected to the driver circuit
  • Both Raspberry Pi and Arduino get supply by connecting both with the Power Bank
  • Matlab installed in Laptop receive lidar scan Values by using ROS Network configuration with ROS software package in Matlab
  • Based on the scan control commands for a car can be sent from laptop Bluetooth to the HC-05 (Bluetooth) in Bot.

Project Description

  • Initially, ROS is connected with the Network (Raspberry Pi)
  • By using ROS network configuration, the environment should be set in Matlab
  • After that Publishing the Laser Scan data from the Lidar
  • Laser scan is received in the Matlab using ROS Network
  • First Mapping is Done by controlling the turtle bot manually from the Matlab
  • After complete mapping is done, will go for Destination Marking
  • In the map, we can plot the destination point in the occupancy grid
  • After fixing the Destination point, path planning Algorithm should be performed, for Path Planning, PRM is used (Probabilistic Road Map)
  • It will plot the possible way to reach the destination, using the number of nodes and its distance between each node.
  • After Path planning is done, Path following is done by making the car to follow the desired path using the coordinates.
  • Every Movement is controlled by the Matlab by sending Bluetooth commands to the turtle bot. At the same time localization is also done to visualize the current position of the Bot.
  • It Automatically follows the path and reaches the destination.

 Hardware Required

  • Raspberry Pi 3
  • SD Card 16 GB class 10
  • RPLidar A1
  • Robo Setup
  • Power Bank  (10000 mAh, 2 A minimum)
  • Arduino UNO
  • HC-05 Bluetooth Module
  • L293D Driver module

Software Required

  • ROS kinetic OS image for Raspberry Pi
  • Matlab, which has a Robotic Operating System Software Package
  • Arduino IDE
  • SD Card Formatter
  • Etcher/win32Disk Imager/Rufus

Application

  • This TurtleBot can be used for indoor service robots
  • It can be used for Delivery robot within the Industry

Result

Mapping

Mapping

Destination Marking in Binary occupancy Grid

Destination marking

Path Planning

Path following ROS Robot

Destination Reaching

Destination reachhing

Additional information

Weight1.000000 kg

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