Sampling-Based Path Planning for Cooperative Autonomous Maritime Vehicles to Reduce Uncertainty in Range-Only Localization
- Resource Type
- Periodical
- Authors
- Willners, J.S.; Toohey, L.; Petillot, Y.
- Source
- IEEE Robotics and Automation Letters IEEE Robot. Autom. Lett. Robotics and Automation Letters, IEEE. 4(4):3987-3994 Oct, 2019
- Subject
- Robotics and Control Systems
Computing and Processing
Components, Circuits, Devices and Systems
Uncertainty
Path planning
Navigation
Robot localization
Autonomous underwater vehicles
Motion planning
Acoustic communication
cooperating robots
localization
marine robotics
motion and path planning
- Language
- ISSN
- 2377-3766
2377-3774
The following letter presents an adaptive path planning algorithm for cooperative localization in the maritime environment. It considers the scenario where an Autonomous Surface Vehicle (ASV) acts as a Communication and Navigation Aid (CNA) to support Autonomous Underwater Vehicles (AUVs) with range measurements. As AUVs have no access to GPS while submerged, range measurements can bind the otherwise continuously growing navigational error. This can be done by methods such as range-only Extended Kalman Filter (EKF). In such methods, the resulting uncertainty and positional error depends on the geometry between transmitter (CNA) and receiver (AUV). This letter proposes a planning algorithm that combines priority based expansion of a search tree with random sampling-based exploration to position the CNA at strategic positions to transmit ranging messages at optimal times to reduce the uncertainty and error at the AUVs’ position. The approach is validated and shows an increased confidence for AUVs’ localization in simulated environments as well as real experiments using a dataset gathered from AUV Sirius.