Khoa "Albert" Vo
Computer science
Hometown: Da Nang, Hai Chau, Vietnam
Graduation date: Spring 2026
FURI | Summer 2025
Bridging the Sim-to-Real Gap in Autonomous Systems Using Learning from Demonstration
This research examines the effectiveness of learning from demonstration (LfD) techniques in transferring knowledge from simulated to real-world environments for complex autonomous driving tasks involving obstacle avoidance. The study utilizes the Duckietown platform to compare LfD approaches given the data combination from simulation and real-world scenarios through metrics including average distance traveled and survival time. Results indicate that simulating data can aid the policy to achieve comparable performance while requiring fewer real-world interactions. This work provides insight into how to leverage task-relevant external data, facilitating effective knowledge transfer from simulation to real-world environments. Future research will explore combining LfD with other transfer techniques or conduct experiments with diverse driving tasks to better understand the effectiveness of this learning approach.
Mentor: Hua Wei
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