PROJECT PROPOSAL
CO-OPERATIVE MAPPING AND LOCALIZATION OF AUTONOMOUS
ROBOTS
LYNTON DICKS
Supervisor: DR. KAREN BRADSHAW Department of Computer Science, Rhodes University
March 2011
1 Principle Investigator
LYNTON DUDLEY DICKS 5 Bedford Street
Grahamstown, 6139 0763825630
Supervised by: DR. KAREN BRADSHAW
2 Project Title
CO-OPERATIVE MAPPING AND LOCALIZATION OF AUTONOMOUS ROBOTS
3 Statement of the Problem
Simultaneous Localization and Mapping (SLAM) is a family of algorithms in robotics that is concerned with the creation and maintenance of maps of previ- ously unknown and unchanging environments and then using those maps to determine the robot’s position within those environments [1]. Co-operative Mapping and Localization of Autonomous Robots extends that definition to work with multiple robots so that there are many robots working together to map an environment. Having multiple robots mapping a larger environment in parallel makes exploration more efficient.
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4 Objective of the Research
The objective of this project is to extend the SLAM framework that was devel- oped in 2010, by Shaun Egan [1], to allow multiple robots to map an area and to allow them to map an area without knowing their starting position relative to each other.
5 History and Background
In 2009, Leslie Luyt developed an ”Autonomous Robotic Programming Frame- work” [3] as part of his honours thesis. This framework is a generic programming framework and combines standard robotic operations with Artificial Intelligence and it abstracts away the details of interfacing with and controlling robots [3].
This framework was written in a way that makes adding new robots or hardware easy to accomplish since all that needs to be done is to implement the specified hardware classes and add them to the inheritance hierarchy under the correct base class.
In 2010, Shaun Egan developed ”A Robotic Framework for use in Simulta- neous Localization and Mapping Algorithms” [1] as part of his honours thesis.
This framework extends Leslie’s framework and adds the SLAM functionality to it. Shaun developed both an online and an offline version of the SLAM framework. The online version of the framework supplies SLAM functionality to the robot in realtime as the robot moves through the environment whereas the offline version of the framework allows data recorded by a robot as it moves through an environment to be analyzed later [1].
6 Approach
To accomplish the goals outlined, I will need to study the frameworks that I am building on top of, as well as the languages that those frameworks use. Test programs will then be written that use those frameworks to gain more famil- iarity with their subtleties and idiosyncrasies. A literature survey will then be undertaken to ascertain how best to extend the SLAM framework in order to add co-operative functionality. Implementation will begin once the choice of algorithm and implementation approach has been chosen. Once implementa- tion and testing is completed, it is hoped that a test involving multiple robots could be undertaken to ascertain the viability and performance of the CSLAM framework.
7 Requirements/Resources
The robot that will be used to develop the framework for CSLAM is a Fis- chertechnik robot. The robot consists of the Fischertechnik Robo TX controller which has a 32-bit ARM 9 processor (200 MHz), a display, and an integrated
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Bluetooth radio interface (2.4 GHz with a range of 10m) [2]. The Bluetooth interface will be used to connect to the robot from the computer and send data and commands between them. In addition, the robot also comes with two ul- trasonic sensors and two encoder motors. The two encoder motors are needed to provide accurate odometry data. Odometry data is data relating to the ac- tual position of the robot through the turning of its wheels. The two ultrasonic sensors are needed to provide range estimation for landmark extraction. The particular ultrasonic sensors that will be used have a range of 5cm to 4m with a resolution of 1cm. The odometry data and landmark data is used to estimate the robot’s position in the environment and to build or update the environment map.
8 Progression Time-line
Deadline Activity
10 March 2011 Studied and practiced using Latex and Bibtex 15 March 2011 Prepare and Present Project Seminar 1 15 March 2011 Complete First Draft of Project Proposal
1 April 2011 Prepare Project Website and upload current documents 10 April 2011 Studied Python 3.2 and studied SLAM framework 24 June 2011 Completed Literature Review
26 June 2011 Present Project Seminar 2
27 June 2011 Begin Design and Implementation of CSLAM 19 September 2011 Short Paper Submitted
31 October 2011 Present Project Seminar 3 7 November 2011 Project Hand-in
14 November 2011 Final Website completed
References
[1] Egan, S. A robotics framework for use in simultaneous localization and mapping algorithms. Honours thesis, Rhodes University, 2010.
[2] Fischertechnik. Fischertechnik robo tx controller.
http://www.fischertechnik.biz/products/edproducts/roboticsproducts/robo- tx-controller.html.
[3] Luyt, L. Autonomous robotic programming framework. Honours thesis, Rhodes University, 2009.
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