Research papers

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

Autonomous Calibration - Wheels & Camera in Duckietown

Autonomous Calibration – Wheels and Camera in Duckietown

Multi-camera multi-robot visual localization system

Visual localization using multi-camera multi-robot system

Analysis of Object Detection Models on Duckietown Robot Based on YOLOv5 Architectures

Object Detection on Duckiebots Using YOLOv5 Models

Survey on Testbeds for Vehicle Autonomy & Robot Swarms

Survey on Testbeds for Vehicle Autonomy & Robot Swarms

Sim2Real Transfer of Multi-Agent Policies for Self-Driving

Sim2Real Transfer of Multi-Agent Policies for Self-Driving

Enhancing Visual Domain Randomization with Real Images for Sim-to-Real Transfer

Enhancing Visual Domain Randomization for Sim2Real Transfer

Leveraging Reward Consistency for Interpretable Feature Discovery in Reinforcement Learning

Reward Consistency for Interpretable Feature Discovery in RL

Vision-based reinforcement learning for lane-tracking control

Vision-based Reinforcement Learning for Lane-Tracking Control

Deep Reinforcement Learning for Autonomous Navigation on Duckietown Platform: Evaluation of Adversarial Robustness

Evaluating Adversarial Robustness in Duckietown Navigation

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

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