Building Maps and Navigation for Autonomous Robots Arindam Khaled AI and Knowledge Based Sys II.

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Presentation transcript:

Building Maps and Navigation for Autonomous Robots Arindam Khaled AI 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.

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