Research papers

Duckietown is a versatile and accessible mobile robotics and embedded AI modular setup for reproducible scientific research.

Robust Reinforcement Learning-based Autonomous Driving Agent for Simulation and Real World

Interactive Learning with Corrective Feedback for Policies based on Deep Neural Networks

Duckietown: An open, inexpensive and flexible platform for autonomy education and research

Learning autonomous systems — An interdisciplinary project-based experience

Deep Trail-Following Robotic Guide Dog in Pedestrian Environments for People who are Blind and Visually Impaired – Learning from Virtual and Real Worlds

Integration of open source platform Duckietown and gesture recognition as an interactive interface for the museum robotic guide

Hybrid control and learning with coresets for autonomous vehicles

Towards blockchain-based robonomics: autonomous agents behavior validation

Learning for Multi-robot Cooperation in Partially Observable Stochastic Environments with Macro-actions

A more comprehensive list of research papers is available on Google Scholar.

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