Research papers using Duckietown
You can find the full list of peer reviewed papers on Google Scholar. If you tell us about your research with Duckietown, we can include it on this page.
Monocular Robot Navigation with Self-Supervised Pretrained Vision Transformers
Monocular Robot Navigation with Self-Supervised Pretrained Vision Transformers Duckietown’s infrastructure is used by researchers worldwide to push the boundaries of knowledge. Of the many outstanding
Learning Autonomy in practice with Vincenzo Polizzi
ETHZ, Zurich, March 11, 2022: How Vincenzo discovered his true professional passion as a student using Duckietown. Learning Autonomy in practice with Vincenzo Polizzi Vincenzo
AI Driving Olympics 2021: Urban League Finalists
AI Driving Olympics 2021 – Urban League Finalists This year’s embodied urban league challenges were lane following (LF), lane following with vehicles (LFV) and lane following
Join the AI Driving Olympics, 6th edition, starting now!
The 2021 AI Driving Olympics Compete in the 2021 edition of the Artificial Intelligence Driving Olympics (AI-DO 6)! The AI-DO serves to benchmark the state
Automatic Wheels and Camera Calibration for Monocular and Differential Mobile Robots
Automatic Wheels and Camera Calibration for Monocular and Differential Mobile Robots Konstantin Chaika, Anton Filatov, Artyom Filatov, Kirill Krinkin Applied Sciences 11, no. 13: 5806.
Embedded out-of-distribution detection on an autonomous robot platform
Embedded out-of-distribution detection on an autonomous robot platform Embedded out-of-distribution detection on an autonomous robot platform Michael Yuhas, Yeli Feng, Daniel Jun Xian Ng, Zahra
AI Driving Olympics 5th edition: results
AI-DO 5: Urban league winners This year’s challenges were lane following (LF), lane following with pedestrians (LFP) and lane following with other vehicles, multibody (LFV_multi). Let’s
AI-DO 5 leaderboard update
AI-DO 5 pre-finals update With the fifth edition of the AI Driving Olympics finals day approaching, 1326 solutions submitted from 94 competitors in three challenges,
Imitation Learning Approach for AI Driving Olympics Trained on Real-world and Simulation Data Simultaneously
Imitation Learning Approach for AI Driving Olympics Trained on Real-world and Simulation Data Simultaneously Mikita Sazanovich, Konstantin Chaika, Kirill Krinkin, Aleksei Shpilman Workshop on AI
Join the AI Driving Olympics, 5th edition, starting now!
Compete in the 5th AI Driving Olympics (AI-DO) The 5th edition of the Artificial Intelligence Driving Olympics (AI-DO 5) has officially started! The AI-DO serves
Integrated Benchmarking and Design for Reproducible and Accessible Evaluation of Robotic Agents
Integrated Benchmarking and Design for Reproducible and Accessible Evaluation of Robotic Agents Jacopo Tani, Andrea F. Daniele, Gianmarco Bernasconi, Amaury Camus, Aleksandar Petrov, Anthony Courchesne,
IROS2020: Watch The Workshop on Benchmarking Progress in Autonomous Driving
What a start for IROS 2020 with the “Benchmarking Progress in Autonomous Driving” workshop! The 2020 edition of the International Conference on Intelligent Robots and
The Workshop on Benchmarking Progress in Autonomous Driving at IROS 2020
The IROS 2020 Workshop on Benchmarking Autonomous Driving Duckietown has also a science mission: to help develop technologies for reproducible benchmarking in robotics. The IROS 2020
Robust Reinforcement Learning-based Autonomous Driving Agent for Simulation and Real World
Title: Robust Reinforcement Learning-based Autonomous Driving Agent for Simulation and Real World – IEEE Conference Publication Authors: Péter Almási, Róbert Moni, Bálint Gyires-Tóth Published: 2020
Community Spotlight: Arian Houshmand – Control Algorithms for Traffic
No one likes sitting in traffic – it is a waste of time and damaging to the environment. Thankfully researcher Arian Houshmand from Boston University CODES
AI-DO 3 – Urban Event Winners
In case you missed it AI-DO 3 has come and gone. Interested in reliving the competition? Here’s the video. We had a great time at NeurIPS
Learning for Multi-robot Cooperation in Partially Observable Stochastic Environments with Macro-actions
Authors: Miao Liu, Kavinayan Sivakumar, Shayegan Omidshafiei, Christopher Amato, Jonathan P. How Published in IROS 2017. Link: https://arxiv.org/abs/1707.07399
Towards blockchain-based robonomics: autonomous agents behavior validation
Authors: Konstantin Danilov, Ruslan Rezin, Alexander Kolotov, Ilya Afanasyev Published on arXiv on May 8, 2018 Link: https://arxiv.org/abs/1805.03241
Hybrid control and learning with coresets for autonomous vehicles
Authors: Guy Rosman, Liam Paull, and Daniela Rus Published in IROS 2017 Link: https://ieeexplore.ieee.org/document/8206612/
Integration of open source platform duckietown and gesture recognition as an interactive interface for the museum robotic guide
Authors: Feng-Ching Cheng, Zi-Yu Wang, and Jee-Jee Chen Published in 2018 Wireless and Optical Communication Conference Link: https://ieeexplore.ieee.org/abstract/document/8372718/
Duckietown: An Innovative Way to Teach Autonomy
Authors: Jacopo Tani, Liam Paull, Maria T. Zuber, Daniela Rus, Jonathan How, John Leonard, Andrea Censi Published in EDURobotics 2016 Link:https://link.springer.com/chapter/10.1007/978-3-319-55553-9_8
Deep Trail-Following Robotic Guide Dog in Pedestrian Environments for People who are Blind and Visually Impaired – Learning from Virtual and Real Worlds
Authors: Tzu-Kuan Chuang, Ni-Ching Lin, Jih-Shi Chen, Chen-Hao Hung, Yi-Wei Huang, Chunchih Teng, Haikun Huang, Lap-Fai Yu, Laura Giarre, and Hsueh-Cheng Wang Published in ICRA