Real-world autonomy in uncertain and unknown environments

Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2025-10-19 without embargo terms

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Aerospace Engineering

Grantor

University of Illinois Urbana-Champaign

Year dc:date

2025

Author dc:creator

• Thangeda, Pranay

Contributors dc:contributor

• Ornik, Melkior
• Tran, Huy T.
• Allison, James
• Hauser, Kris K.

• Autonomous Systems
• Robotics
• Space Robotics
• Mars Rover Navigation
• Planetary Rovers
• Unmanned Systems
• Artificial Intelligence (AI)
• Machine Learning
• Reinforcement Learning
• Efficient Learning
• Accelerated Learning
• Planning under Uncertainty
• Decision-Theoretic Planning
• Markov Decision Processes (MDPs)
• Stochastic Control
• Unknown Environments
• Stochastic Environments
• Unknown Dynamics
• Side Information Integration
• Indirect Sampling
• Sample Efficiency
• Exploration-Exploitation
• Bayesian Exploration
• Value of Information
• Agent Safety
• Safety Guarantees
• Safe Reinforcement Learning
• Optimal Routing
• Stochastic Travel Times
• Spatial Correlations
• Multiobjective Optimization
• Onboard Sensors
• Real-time Data

Statement dc:rights

• Copyright 2025 Pranay Thangeda

Language dc:language

en, eng

Handle dc:identifier

https://hdl.handle.net/2142/129472

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/129472