Mobile robot project

Autonomous Floor Mapping

2010 - 2011 spring

Abstract

Simulation can be used to reduce the time and cost to develop a new technology. This paper describes the development of an autonomous floor mapping robot. In order to reduce the cost of building prototypes to test the program, we used the Simbad 3D simulator. To test in a more realistic environment, we established a way to control objects in a virtual world Second Life. Then, for the hardware part, we built a low cost robot with cheap but accurate Sharp IR sensors with a regular optical mouse.

Introduction

Motivations

• • Robots need maps for efficient paths planning

  • Mapping is costly

    • US $6,000 for SICK LMS-200

  • Need a platform to test our algorithm for floor mapping

    • Software

    • Hardware

Objectives

• • Algorithm

    • Easy to implement

    • Practical

  • Robot platform

    • Arduino based .  easy to extend and customize

    • Cheap sensors for 2D scanning

    • Easy and cheap way to track robot’s location

Algorithm

Initialization

• 1. Divide the environment into grids

  2. Go straight

  3. While going straight, perform a 180-degree before moving to the new grid

  4. Record whether the left, right, and front grids are occupied or not

  5. Continue steps 2-4 until the front grid is occupied,  then enter the main loop

Main Loop

WHILE (unexplored grid exists)

IF no block in front & not explored in front

IF no block on left & not explored on left

turn left

go straight

ELSE

go straight 

ELSE

IF no block on left & not explored on left

turn left

go straight

ELSE IF no block on right & not explored on right

turn right

go straight

ELSE

Breath first search to find an unexplored grid

Assumptions

• • The mapping environment must have a closed boundary

    • Required to terminate the main loop

  • Each grid is as large as the robot

Software SimulatioSimbad 3D Robot Simulator

• • software simulator

  • Advantages:

    • Source code is available → modify the code to create our own interface and environment

    • Very fast to obtain the sensors’ readings

    • Location and orientation of the robot are accurately obtained

Second Life

• • Virtual World for the simulation

  • Problems

    • Hard to track location accurately

    • Hard to obtain the map of the surroundings

    • It takes one minute to do a 180-degree scan

  • Cannot map the environment reliably and autonomously

Real robot

Hardware Components

• • Control

    • Two Arduino boards

  • Sensing

    • Three Sharp IR analog distance sensors      (10 .- 80 cm)

    • Computer mouse

    • Digital compass

  • Communication

    • Two Xbee modules

Assembled Robot

Scanning, Tracking, talking

• • IR Sensors for Scanning

Mouse for Tracking

• • Robot moves in incremental steps

  • Mouse keeps track of robot’s movement and helps adjusting the robot’s path

Xbee for Communication

• • Two Xbee modules

    • On robot

    • Connected to computer

  • Xbees are used to send

    • commands from computer to robot

    • sensors’ readings from robot to computer for processing

Results and Summary

Results

• • IR sensors give really good readings

    • Useful for pose estimation (future work)

  • Incremental steps and mouse make robot go very straight

  • Magnetic fields nearby interfere with compass’s readings

    • Robot does not turn left or right perfectly

Discussion

• • Using software simulations to experiment with algorithms

  • Extendable robot for US $400

    • Xbee, mouse, multiple IR sensors, compass, …

  • Accurate 2D scans can be accomplished for under US $65

  • Computer mouse is used beyond its intended purposes

Summary

• • Easy-to-implement mapping algorithm

  • Simbad 3D Robot Simulator for simulation

  • Cheap robot platform for testing

    • IR sensors for scanning

    • Mouse and compass for tracking

    • Xbee for wireless communication

Publication

• H. Nguyen, A. Eguchi, D. Hooten, "In Search of a Cost Effective Way to Develop Autonomous Floor Mapping Robots,"9th IEEE International Symposium on RObotic and Sensors Environments (ROSE 2011), 2011, Montreal, Canada. pp.107-112. [View Download]