Autonomous mapping robot using odometry and sonar sensors

The AUTONOMOUS MAPPING ROBOT (AMR) was developed with the aim of contracting a prototype of a robot that could generate a 2D map of a given environment using an array of ultrasonic sensors commonly known as sonars. To fulfill this, the group has employed the use of several devices that can send and...

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Bibliographic Details
Main Authors: Arciaga, Ramiro M., Cuevas, Andro T., Tan, Herbert Hugh O., Tumbaga, Edward C., Wong, Anthony Benson R.
Format: text
Language:English
Published: Animo Repository 2006
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Online Access:https://animorepository.dlsu.edu.ph/etd_bachelors/14576
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Institution: De La Salle University
Language: English
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Summary:The AUTONOMOUS MAPPING ROBOT (AMR) was developed with the aim of contracting a prototype of a robot that could generate a 2D map of a given environment using an array of ultrasonic sensors commonly known as sonars. To fulfill this, the group has employed the use of several devices that can send and receive data via Inter-IC Bus (I C). I C, pronounced as I-squared-C is a way that integrated circuitry communicates with each other without physical connection. The IC used for the components is PICI6F87. The most important component for fulfilling the objective is the SRF08 ultrasonic sensor. Five of them are strategically arranged around the robot's platform to optimally get distances from the obstacles around the environment. To get the robot's coordinates at any given time, a magnetic compass based on the Earth's magnetic field (CMPSO3) and the encoders built-in on the EMG30 motors are used. The heart of the robot lies on the motor controller MD23. It acts as the 5V power supply as well as the data (SDA) and clock (SCL) connection between all the other devices and the CM02 transmitter. Connected to the PC is the RF04 receiver completing the loop. All the data gathered are passed to the PC via the telemetry pair where all the processing happens, both commanding the robot and generating the 2D map of the environment. AMR runs a repetitive cycle of getting distances from obstacles nearby, basing it in its current location, plotting the data gathered to generate a portion of the map and finally, planning for subsequent action.