Tristan Kyzer

Date of Award

Spring 2021

Document Type

Open Access Thesis

Department

Mechanical Engineering

First Advisor

Yi Wang

Abstract

Localization of robotic systems is a necessity for control of robotic systems and often requires the use of costly sensors and equipment onboard the robot or installed within a facility. GPS or GNSS sensors are effective for localizing robots in GPSaccessible environments, but do not work as well in dense urban areas or inside fully enclosed buildings, such as factories or warehouses. Sensors such as LiDAR can be costly and require substantial experience and knowledge to utilize as well as potential changes to infrastructure for use. Computer vision-based localization systems offer potential as a localization solution for various applications. A low-cost overhead camera system was developed to localize robotic systems in an indoor facility, aiding the development and verification of algorithms. A visual servoing path following robot was built and developed utilizing Robot Operating System to examine the computer visionbased localization camera system. A track was designed and assembled, and low-cost cameras were mounted in an overhead configuration. A program to track the robots’ position was developed utilizing multiple camera feeds, open-source computer vision tools, and fiducial marker tracking. Utilizing the camera feed from three different cameras and ArUco fiducial markers, localization of a robotic system was conducted in static positions with an average of 0.80% error between the physical measurement and measurement made by the camera system. The path following robot was tracked and the RMS position acquired by the developed localization system compared to that captured by the robot’s onboard camera with an average difference of 1.04 cm.

Rights

© 2021, Tristan Kyzer

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