BE_Project_2012

Title: Localization and Mapping with a Mobile Robot and Kinect

Group Info:

College: Fr. Conceicao Rodrigues College of Engineering, University of Mumbai

• Ashish Belokar (Computer Engineering)
• Kshitij Dholakia (Computer Engineering)
• Swapnil Kate (Computer Engineering)

Extension Of

Implementation of slam_gmapping

Project Description

The project involves the development of a mobile robotic platform, equipped with wheel encoders and Kinect sensor and using it to carry out Localization and Mapping in indoor environments.

Key implementation points in the project are:

•   Developing mobile robot
  

•   Converting encoder data to pose estimates (x, y, theta)
  

•   Identifying Coordinate frames of the robot, and implementing Coordinate frame Transformations
  

•   Set up the Kinect to stream Laser Scan data from it's depth camera
  

•   Perform slam_gmapping
  

•   Visualize the entire process
  

Technologies Used

•   Robot Operating System
  

•   Kinect
  

•   Arduino
  

•   Custom-made Robot:    
    + Differential (rear-wheel) drive with a front castor-wheel   
    + Laptop-mountable Chasis
  

Installation Instructions

1. Install Robot Operating System on Ubuntu 11.10 ROS Electric
   sudo apt-get install ros-electric-desktop-full

2. Install OpenNI, the Kinect driver, as a ROS Stack OpenNI
   sudo apt-get install ros-electric-openni-kinect

3. Download the Arduino IDE, for programming the Arduino microcontroller Arduino IDE
   sudo apt-get install arduino

4. Set up Arduino to run as a ROS node using rosserial rosserial
   hg clone https://kforge.ros.org/rosserial/hg

5. Set up pointcloud_to_laserscan ROS package pointcloud_to_laserscan
   hg clone https://kforge.ros.org/turtlebot/turtlebot

References

• Robot Operating System Tutorials

• Arduino Tutorials

• rosserial Tutorials

• Coordinate Frames Transformation

• OpenNI Reference

• Turtlebot Demos

• slam_gmapping

• SLAM References (Analytical)

  1. OpenSLAM, a collection of open source SLAM algorithms
  2. SLAM for dummies, an introduction to SLAM

Video Links

• demo
• screencast