Roboat II: A Novel Autonomous Surface Vessel for Urban Environments
Name
2007.10220.pdf
Description
Submitted version
Size
3.81 MB
Format
Adobe PDF
Checksum (MD5)
5ad57e8fd36453ef895cefa3bff27006
Author(s)
Wang, Wei
Shan, Tixiao
Leoni, Pietro
Fernandez-Gutierrez, David
Meyers, Drew
Ratti, Carlo
Rus, Daniela
Date Issued
2020
Journal
IEEE International Conference on Intelligent Robots and Systems
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Wang, Wei, Shan, Tixiao, Leoni, Pietro, Fernandez-Gutierrez, David, Meyers, Drew et al. 2020. "Roboat II: A Novel Autonomous Surface Vessel for Urban Environments." IEEE International Conference on Intelligent Robots and Systems.
Version
Original manuscript
Abstract
© 2020 IEEE. This paper presents a novel autonomous surface vessel (ASV), called Roboat II for urban transportation. Roboat II is capable of accurate simultaneous localization and mapping (SLAM), receding horizon tracking control and estimation, and path planning. Roboat II is designed to maximize the internal space for transport, and can carry payloads several times of its own weight. Moreover, it is capable of holonomic motions to facilitate transporting, docking, and inter-connectivity between boats. The proposed SLAM system receives sensor data from a 3D LiDAR, an IMU, and a GPS, and utilizes a factor graph to tackle the multi-sensor fusion problem. To cope with the complex dynamics in the water, Roboat II employs an online nonlinear model predictive controller (NMPC), where we experimentally estimated the dynamical model of the vessel in order to achieve superior performance for tracking control. The states of Roboat II are simultaneously estimated using a nonlinear moving horizon estimation (NMHE) algorithm. Experiments demonstrate that Roboat II is able to successfully perform online mapping and localization, plan its path and robustly track the planned trajectory in the confined river, implying that this autonomous vessel holds the promise on potential applications in transporting humans and goods in many of the waterways nowadays.
MIT Department
Senseable City Laboratory
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1109/IROS45743.2020.9340712
