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

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 NC...

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Bibliographic Details
Published in:arXiv.org 2019-10
Main Authors: Yi-Wei, Huang, Chuang, Tzu-Kuan, Ni-Ching, Lin, Yu-Chieh Hsiao, Pin-Wei, Chen, Ching-Tang, Hung, Shih-Hsing, Liu, Hsiao-Sheng, Chen, Hsieh, Ya-Hsiu, Yen-Hsiang, Huang, Yu-Xuan, Chen, Kuan-Lin, Chen, Ya-Jou Lan, Chao-Chun, Hsu, Chun-Yi, Lin, Li, Jhih-Ying, Huang, Jui-Te, Yu-Jen Menn, Sin-Kiat Lim, Kim-Boon, Lua, Chia-Hung Dylan Tsai, Chi-Fang, Chen, Hsueh-Cheng, Wang
Format: Article
Language:English
Subjects:
Computer simulation
Obstacle avoidance
Surface vehicles
Online Access:Get full text
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Summary: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.
ISSN:2331-8422