Title: Edge Detection by Centimeter Scale Low-Cost Mobile Robots

Abstract:

In Search and Rescue (SaR) efforts after natural disasters like earthquakes, the primary focus is to find and rescue people in building rubble. These rescue efforts could put first responders at risk and are slow due to the unstable nature of the environment. Robotic solutions capable of gathering information are useful because they can provide environment information to the first responders that decrease the risks of rescue efforts. However, navigating a post-disaster environment is an unsafe task by nature because depending on the size and capability of the robots, they may get stuck, lost, or damaged in unpredictable situations, which can be very costly when using expensive robots.

With this thesis, we present the implementation of two low cost sensors, i.e., a photoresistor and an ultrasonic sensor, onto an existing low-cost, small-scale mobile robotic system. We implement these sensors to give the robot the ability to navigate unknown environments and map the gaps. The low-cost nature makes these robots an ideal candidate for navigating near edges – even in the event that the robot falls off the edge, there is little monetary loss. After presenting mechanical and electrical changes needed to accommodate these sensors onto the robot, we present three algorithms to detect an edge, that perform with varying safety levels and mapping capabilities. We then demonstrate the results of these algorithms in simulation environments where the robot is traversing a convex platform. These algorithms successfully gather new information about the platform and provide maps that would make future traversal of the environment safer.

Committee:

Zeynep Temel (advisor)

Wennie Tabib

Brady Moon