Model Predictive Control of underwater floating-base manipulator systems in rough seas

Design a new control technique to enable underwater vehicles to perform manipulation operations in wave-perturbed climates
Description of the Project: 

Despite recent advances in underwater technology, autonomous operation of unmanned underwater vehicles in complex submerged environments and in harsh climate still remains an unsolved problem. The degree of automation in the offshore sector currently remains limited due to the complexity of performing even the simplest station-keeping tasks when subject to wave and currents dominated scenarios. This has a significant impact on the chance to perform systematic and accurate maintenance and inspection operation of submerged structures, with remarkable implications on the survivability and cost of running of oil rigs, renewable energy plants, etc.

This project aims to exploit Model Predictive Control techniques supplemented with accurate, real-time wave data to perform precise compensation of the hydrodynamic disturbances over a short-range control temporal-horizon. Based on this approach, the vehicle will be able to estimate wave perturbations and implement these in the control input over a short time frame. This will enable to perform accurate station-keeping and enable improved manipulation accuracy even in moderately adverse weather.

Resources required: 
The work will mainly entail modelling/control effort, so there will be no need to rely on an actual hardware platform. However, there might be the chance for the student to run preliminary tests in the FloWave tank at UoE with an OpenROV or a Trident open source unmanned robotic platforms.
Project number: 
100004
First Supervisor: 
University: 
Heriot-Watt University
Second Supervisor(s): 
First supervisor university: 
Heriot-Watt University
Essential skills and knowledge: 
The work will mainly entail modelling/control effort, so there will be no need to rely on an actual hardware platform. However, there might be the chance for the student to run preliminary tests in the FloWave tank at UoE with an OpenROV or a Trident open source unmanned robotic platforms.
Desirable skills and knowledge: 
Some basic knowledge in hydrodynamics
References: 

1) D. C. Fernández and G. A. Hollinger, 2017, Model Predictive Control for Underwater Robots in Ocean Waves, in IEEE Robotics and Automation Letters, vol. 2, no. 1, pp. 88-95. doi: 10.1109/LRA.2016.2531792

2) Barbalata, C., Dunnigan, M. W. & Petillot, Y., 2018, Position/force operational space control for underwater manipulation, Robotics and Autonomous Systems. 100, p. 150-159 10 p.

3)  Barbalata, C., De Carolis, V., Dunnigan, M. W., Pétillot, Y. & Lane, D., 2015, An adaptive controller for autonomous underwater vehicles, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2015. IEEE, p. 1658-1663 6 p. 7353590.

4) Barbalata, C., Dunnigan, M. W. & Pétillot, Y., 2015, Reduction of the dynamic coupling in an underwater vehicle-manipulator system using an inverse dynamic model approach, IFAC Proceedings Volumes, Vol. 48-2, p. 44-49 6 p.