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Team NCTU: Toward AI-Driving for Autonomous Surface Vehicles -- From Duckietown to RobotX

Authors :
Huang, Yi-Wei
Chuang, Tzu-Kuan
Lin, Ni-Ching
Hsiao, Yu-Chieh
Chen, Pin-Wei
Hung, Ching-Tang
Liu, Shih-Hsing
Chen, Hsiao-Sheng
Hsieh, Ya-Hsiu
Huang, Yen-Hsiang
Chen, Yu-Xuan
Chen, Kuan-Lin
Lan, Ya-Jou
Hsu, Chao-Chun
Lin, Chun-Yi
Li, Jhih-Ying
Huang, Jui-Te
Menn, Yu-Jen
Lim, Sin-Kiat
Lua, Kim-Boon
Tsai, Chia-Hung Dylan
Chen, Chi-Fang
Wang, Hsueh-Cheng
Publication Year :
2019
Publisher :
arXiv, 2019.

Abstract

Robotic software and hardware systems of autonomous surface vehicles have been developed in transportation, military, and ocean researches for decades. Previous efforts in RobotX Challenges 2014 and 2016 facilitates the developments for important tasks such as obstacle avoidance and docking. Team NCTU is motivated by the AI Driving Olympics (AI-DO) developed by the Duckietown community, and adopts the principles to RobotX challenge. With the containerization (Docker) and uniformed AI agent (with observations and actions), we could better 1) integrate solutions developed in different middlewares (ROS and MOOS), 2) develop essential functionalities of from simulation (Gazebo) to real robots (either miniaturized or full-sized WAM-V), and 3) compare different approaches either from classic model-based or learning-based. Finally, we setup an outdoor on-surface platform with localization services for evaluation. Some of the preliminary results will be presented for the Team NCTU participations of the RobotX competition in Hawaii in 2018.

Details

Database :
OpenAIRE
Accession number :
edsair.doi.dedup.....d6017a848ee83d282feb151920905208
Full Text :
https://doi.org/10.48550/arxiv.1910.14540