Electrical Engineering
      and Computer Sciences

Electrical Engineering and Computer Sciences

COLLEGE OF ENGINEERING

UC Berkeley

Autonomous Navigation and Collision Avoidance of a Scale Model Robot Using Smartphone Sensors

Garen Der-Khachadourian

EECS Department
University of California, Berkeley
Technical Report No. UCB/EECS-2013-75
May 16, 2013

http://www.eecs.berkeley.edu/Pubs/TechRpts/2013/EECS-2013-75.pdf

Driver-assistance systems and fully autonomous vehicles could address the global challenges of traffic congestion and reduced road capacity. Although the field of autonomous transportation is growing rapidly, system complexity and cost have delayed progress. This project attempts to mitigate these issues through the development of a scale model robot that utilizes the sensors of smartphones for autonomous navigation and collision avoidance. Designing a model robotic system is simpler and more cost-effective than developing one for a full-sized vehicle. This project investigates the possibility of using smartphones sensors as a viable alternative to high-end, expensive sensors. The system utilizes the Orca Robotics software framework, which provides a library of modular and customizable components. The results from this study suggest that integrating smartphone sensors is much more challenging than using standalone devices. Further work is needed to confirm the feasibility of using these sensors. Ideally, as smartphones continue to improve in computational power and sensor accuracy, it will be possible to use them as integral components in autonomous systems.

Advisor: Bernhard Boser


BibTeX citation:

@mastersthesis{Der-Khachadourian:EECS-2013-75,
    Author = {Der-Khachadourian, Garen},
    Title = {Autonomous Navigation and Collision Avoidance of a Scale Model Robot Using Smartphone Sensors},
    School = {EECS Department, University of California, Berkeley},
    Year = {2013},
    Month = {May},
    URL = {http://www.eecs.berkeley.edu/Pubs/TechRpts/2013/EECS-2013-75.html},
    Number = {UCB/EECS-2013-75},
    Abstract = {Driver-assistance systems and fully autonomous vehicles could address the global challenges of traffic congestion and reduced road capacity. Although the field of autonomous transportation is growing rapidly, system complexity and cost have delayed progress. This project attempts to mitigate these issues through the development of a scale model robot that utilizes the sensors of smartphones for autonomous navigation and collision avoidance. Designing a model robotic system is simpler and more cost-effective than developing one for a full-sized vehicle. This project investigates the possibility of using smartphones sensors as a viable alternative to high-end, expensive sensors. The system utilizes the Orca Robotics software framework, which provides a library of modular and customizable components. The results from this study suggest that integrating smartphone sensors is much more challenging than using standalone devices. Further work is needed to confirm the feasibility of using these sensors. Ideally, as smartphones continue to improve in computational power and sensor accuracy, it will be possible to use them as integral components in autonomous systems.}
}

EndNote citation:

%0 Thesis
%A Der-Khachadourian, Garen
%T Autonomous Navigation and Collision Avoidance of a Scale Model Robot Using Smartphone Sensors
%I EECS Department, University of California, Berkeley
%D 2013
%8 May 16
%@ UCB/EECS-2013-75
%U http://www.eecs.berkeley.edu/Pubs/TechRpts/2013/EECS-2013-75.html
%F Der-Khachadourian:EECS-2013-75