Paper Info
Title
Roboat: An Autonomous Surface Vehicle For Urban Waterways
Abstract
Unmanned surface vehicles (USVs) are typically designed for open area marine applications. In this paper, we present a new autonomy system (Roboat) for urban waterways which requires robust localization, perception, planning, and control. A novel localization system, based on the extended Kalman filter (EKF), is proposed for USVs, which utilizes LiDAR, camera, and IMU to provide a decimeter-level precision in dynamic GPS-attenuated urban waterways. Area and shape filters are proposed to crop water reflections and street obstacles from a pointcloud. Euclidean clustering and multi-object contour tracking are then introduced to detect and track the static and moving objects reliably in urban waters. An efficient path planner is tailored to calculate optimal trajectories to avoid these static and dynamic obstacles. Lastly, a nonlinear model predictive control (NMPC) scheme with full state integration is formulated for the four-control-input robot to accurately track the trajectory from the planner in rough water. Extensive experiments show that the robot is able to autonomously navigate in both the indoor waterway and the cluttered outdoor waterway in the presence of static and dynamic obstacles, implying that Roboat could have a great impact on the future of transportation in many coastal and riverside cities.
Year
DOI
Venue
2019
10.1109/IROS40897.2019.8968131
2019 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS)
Field
DocType
ISSN
Computer vision,Extended Kalman filter,Computer science,Model predictive control,Planner,Lidar,Artificial intelligence,Inertial measurement unit,Cluster analysis,Robot,Trajectory
Conference
2153-0858
Citations 
PageRank 
References 
0
0.34
0
Authors
6
Name
Order
Citations
PageRank
Wei Wang1324.22
Banti Gheneti200.34
Luis A. Mateos300.34
Fabio Duarte462.51
Carlo Ratti51211113.38
Daniela Rus67128657.33