Object detection and sensor data processing for off-road autonomous vehicles

Author

Timothy FosterFollow

Issuing Body

Mississippi State University

Advisor

Ball, John

Committee Member

Gurbuz, Ali

Committee Member

Tang, Bo

Date of Degree

4-30-2021

Original embargo terms

Worldwide

Document Type

Graduate Thesis - Open Access

Major

Computer Engineering

Degree Name

Master of Science

College

James Worth Bagley College of Engineering

Department

Department of Electrical and Computer Engineering

Abstract

Autonomous vehicles require intelligent systems to perceive and navigate unstructured envi- ronments. The scope of this project is to improve and develop algorithms and methods to support autonomy in the off-road problem space. This work explores computer vision architectures to support real-time object detection. Furthermore, this project explores multimodal deep fusion and sensor processing for off-road object detection. The networks are compared to and based off of the SqueezeSeg architecture. The MAVS simulator was utilized for data collection and semantic ground truth. The results indicate improvements from the SqueezeSeg performance metrics.

Sponsorship

Engineering Research and Development Center Vicksburg

Recommended Citation

Foster, Timothy, "Object detection and sensor data processing for off-road autonomous vehicles" (2021). Theses and Dissertations. 5105.
https://scholarsjunction.msstate.edu/td/5105