Cooperative navigation between surface and sub-surface vehicles

This thesis aims to improve autonomy and reliability in marine robots. This is achieved by combining path planning and acoustic localisation into cooperative navigation. Within path planning it is important that the robot’s found path is feasible, collision-free and can be planned in real-time. This thesis reviews state-of-the-art approaches within the field of path planning along with proposing novel approaches for optimal planning under motion constraints for both goal-based and cooperative scenarios. The aim for cooperative scenarios is to support submerged vehicles with acoustic messages which can be used for localisation. This is an important problem for robots while subsurface, as it is a GPS-denied environment. Conventionally acoustic localisation has been performed by manually deploying static acoustic beacons which require extensive calibration and suffer from an operational area limited by the acoustic range of the transponders or USBL. This thesis presents 3 major novel contributions to the field. The first one is a start to-goal real-time path planner with path repairing capabilities for vehicles to operate in unknown environments. This extension to Hybrid-State A* makes it more useful for both planning in known and unknown environment showing a reduced computational time compared to re-planning. The second contribution presented is a leader-follower planner, where an AUV act as the leader and an ASV follows them to reduce the distance over time. This work takes the motion constraints into consideration such that it can handle all cases where the vehicle operates at different speeds, making it more generic and easier apply to multiple scenarios than classic control methods. The third major work presented is planning for cooperative missions where an ASV plans a path to position itself to reduce the navigational error on an arbitrary amount of AUVs. This work is adaptable both to the scenarios as well as the computational power on the ASV. It shows to in worst case perform as well as compared methods and in most cases outperform them by reducing the error on the AUVs with up to 60%. The results of this thesis show an improvement in the field through a combination of simulated and real data.

Grantor dc:publisher

Heriot-Watt University

Year dc:date.issued

2020

Author dc:creator

• Scharff Willners, Jonatan

Advisor dc:contributor.advisor

• Petillot, Yvan R.

Language dc:language.iso

en

Handle dc:identifier.uri

http://hdl.handle.net/10399/5015

OAI identifier oai:identifier

oai:ros.hw.ac.uk:10399/5015