TurtleBot SLAM

Navigation of TurtleBot using hand-gestures to find target locations marked with AR codes and/or to find a specific person using face-recognition.

The project was showcased and well-received by public at the Museum of Science & Industry (MSI) in Chicago and at the MSR Open House 2016.

Project Overview:

This project consists of following 4 tasks:

  1. Determine number of fingers (gestured) in front of an ASUS Xtion Pro camera
  2. Navigate TurtleBot in an unknown environment using RGB-D SLAM approach, concurrently building a 3D map of the environment; the robot first finds a target station marked with AR code matching the number detected in (1) and then moves towards the target station
  3. Capture, train and recognize faces of people in real-time using a simple GUI
  4. Move the robot to various stations to find a specific person from the database built in (3)

The overall execution of the project is summarised in the poster below:

tbotnav_poster_adj

 

Project Website:

A tutorial on launching the project with your TurtleBot is available on GitHub – http://github.com/patilnabhi/tbotnav

Project Objectives:

  • To explore ROS’ navigation stack – understand and implement localization techniques such as (Bayes’/Kalman/Particle filters), motion planning algorithms (Dijkstra’s/A*), perception using Kinect, and SLAM techniques (Graph SLAM – gmapping / RGB-D SLAM)
  • To integrate following computer vision interfaces in making the TurtleBot SLAM project more exciting:
  1. Hand-gesture recognition:  Using a Kinect, OpenCV and ROS, develop an API to recognize number of fingers from 0 to 5

  2. Face recognition: Using a webcam, OpenCV and ROS, develop an API to create a database of people’s faces and recognize faces in real-time

Future work:

  • Object tracking: Replace AR code tracking and get TurtleBot to find specific objects in the environment
  • RTAB-Map & beyond: Explore the capabilities of RTAB-Map and RGB-D SLAM to make the navigation more robust
  • Simple is beautiful: Improve the overall execution of the project to make it more user interactive by making it simpler/easier

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