Learning methods for robust localization

Thesis

Location awareness is a fundamental need for intelligent systems, such as self-driving vehicles, delivery drones, and mobile devices. Given their on-board sensors (e.g. camera, inertial sensor and LIDAR), previous researchers have developed a variety of localization systems, by building hand-crafted models and algorithms. Under ideal conditions, these sensors and models are able to accurately estimate system states without time bound. However, in real-world environments, many issues such a...

Expand abstract

Authors: Chen, C

• Type of award: DPhil
• Level of award: Doctoral
• Awarding institution: University of Oxford
• Language: English
• Keywords: Localization; Deep Learning; Visual-inertial Odometry; Inertial Navigation; Domain Adaptation; Sensor Fusion
• Subjects: Machine Learning; Robotics; Cyber-Physical Systems