Building Maps and Navigation for Autonomous Robots

Arindam KhaledAI and Knowledge Based Sys II

Purpose

• To design and implement an autonomous learning agent.

• To understand the difficulty, labor, and knowledge involved in designing an autonomous robot.– Hardware and software systems.– To study and understand a few theories on robot

navigation from the literature.

Project Goals

• Let the autonomous robot build map of the closed environment.

• Given the starting co-ordinate and end co-ordinate, devise a program such that the robot can navigate from its starting position to the destination.

• Later, once a working version is released upload this version in youtube and possibly publish a paper!

Architecture(hardware)• LEGO Mindstorm NXT toolkit.

– Primary components:• Three servo motors: Two to move the robot and one to rotate the sonar(s).• Sonar: Right now the robot has only one sonar. But one more sonar is planned

to be added for better readings.• Touch sensor: In case the sonars fail to detect an obstacle or the sonars are

pointed not towards the direction of the movement and an obstacle exists in that direction.

• Color sensor: A color sensor is planned to be used to determine the boundaries.

• Microcontroller: It executes the programs, controls the motors and receives data from the sensors.

• Bluetooth enabled PC: It will communicate with the robot’s microcontrolled.

Semi-Final Version

Software

• RobotC: It is used to create programs for the microcontroller.

• Anders’ Mindstorm: It is an open source software for LEGO Mindstorm. This will be used for bluetooth communication.

A high level process diagram for Building Maps

Navigation

• Use A* based, genetic, and other algorithms found in the literature as the time permits.

A novel concept (Most probably)

• If the current location is not predefined then use neural nets to detect the current location.

• If time permits then this approach will be further explored.

Knowledge

• The algorithms for map building and navigation, and the empirical evidence.

• In the neural nets.

References

• http://www.norgesgade14.dk/bluetoothlibrary.php

• http://www.nxtprograms.com/explorer/index.html