Date of Award

2020

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Computer Science

Committee Chair

Ramazan S. Aygun

Committee Member

Farbod Fahimi

Committee Member

Letha H. Etzkorn

Committee Member

Tathagata Mukherjee

Committee Member

Haeyoung Chung

Subject(s)

Robot vision, Robots--Control systems

Abstract

This dissertation proposes a new method for real time vision-based localization in the full 360-degree area around a 3D reference object. In the past, Mirage pose estimation was developed for multi-camera systems. To achieve 360-degree localization with a single camera, we introduce the Mirage-S pose estimation method that uses a single camera given a 3D reference object as input. Mirage-S finds the solution by using an iterative numerical method with non-linear equations. This dissertation splits the localization problem into three parts: 360-degree 3D object recognition, 360-degree pose estimation, and 360-degree localization application. First, 360-degree 3D object recognition is required to recognize a reference 3D object from all possible 360 degree locations. Second, we use Mirage-S for 360-degree pose estimation to calculate the pose of a robot at all possible 360 degree locations around the reference 3D object. Third, a 360-degree localization application is integrated with a closed-loop real-time trajectory tracking controller. This application expects the mobile robot to move on a desired path covering the whole 360-degree area around the 3D reference object. The outcome of the simulations and real experiments using noise and noise-free information are presented to evaluate the performance of Mirage-S. The results are compared to eight well-known Perspective-n-Point(PnP) methods and Mirage with multiple camera systems. Furthermore, the comparison of the real experimental results between Mirage-S and PoseNet, a learning-based architecture that regressed the absolute pose using a deep convolutional neural network is presented. The successful results of the simulations and real experiments of trajectory tracking are provided.

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