ICONDENSATION: Unifying Low-Level and High-Level Tracking in a Stochastic Framework
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume I - Volume I
Techniques for Deep Sea Near Bottom Survey Using an Autonomous Underwater Vehicle
International Journal of Robotics Research
Distributed maximum a posteriori estimation for multi-robot cooperative localization
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Cooperative localization for autonomous underwater vehicles
Cooperative localization for autonomous underwater vehicles
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Modeling mobile robot motion with polar representations
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Performance analysis of multirobot Cooperative localization
IEEE Transactions on Robotics
iSAM: Incremental Smoothing and Mapping
IEEE Transactions on Robotics
AIS'11 Proceedings of the Second international conference on Autonomous and intelligent systems
Applications of marine robotic vehicles
Intelligent Service Robotics
Adaptive autonomous underwater vehicles for littoral surveillance
Intelligent Service Robotics
Uncertainty-based localization solution for under-ice autonomous underwater vehicles
Proceedings of the Sixth ACM International Workshop on Underwater Networks
Real-time collaborative tracking for underwater networked systems
Proceedings of the Seventh ACM International Conference on Underwater Networks and Systems
Underwater Localization and Environment Mapping Using Wireless Robots
Wireless Personal Communications: An International Journal
Minimizing position uncertainty for under-ice autonomous underwater vehicles
Computer Networks: The International Journal of Computer and Telecommunications Networking
Hi-index | 0.00 |
In this paper we describe the experimental implementation of an online algorithm for cooperative localization of submerged autonomous underwater vehicles (AUVs) supported by an autonomous surface craft. Maintaining accurate localization of an AUV is difficult because electronic signals, such as GPS, are highly attenuated by water. The usual solution to the problem is to utilize expensive navigation sensors to slow the rate of dead-reckoning divergence. We investigate an alternative approach that utilizes the position information of a surface vehicle to bound the error and uncertainty of the on-board position estimates of a low-cost AUV. This approach uses the Woods Hole Oceanographic Institution (WHOI) acoustic modem to exchange vehicle location estimates while simultaneously estimating inter-vehicle range. A study of the system observability is presented so as to motivate both the choice of filtering approach and surface vehicle path planning. The first contribution of this paper is to the presentation of an experiment in which an extended Kalman filter (EKF) implementation of the concept ran online on-board an OceanServer Iver2 AUV while supported by an autonomous surface vehicle moving adaptively. The second contribution of this paper is to provide a quantitative performance comparison of three estimators: particle filtering (PF), non-linear least-squares optimization (NLS), and the EKF for a mission using three autonomous surface craft (two operating in the AUV role). Our results indicate that the PF and NLS estimators outperform the EKF, with NLS providing the best performance.