Mark Anthony Preece
Papers
2
Total Citations
2
H-Index
1
About
Mark Anthony Preece is a leading researcher at the intersection of marine robotics and sustainable aquaculture, specializing in the autonomous operation of Unmanned Underwater Vehicles (UUVs) for offshore fish farm inspection. His work directly addresses the critical challenges of deploying robots in harsh, real-world environments, moving beyond theoretical control to practical, energy-efficient solutions. Preece’s major contributions include the development of a high-fidelity simulation platform for visual inspection of net-pens, which enables safe, thorough testing of autonomous systems before costly and risky field deployment. He further advanced the field by pioneering an energy-optimal Model Predictive Control (MPC) framework, solving the complex non-convex optimization problem to minimize real power consumption during inspection missions. This work is vital for extending UUV operational endurance and reducing costs in commercial aquaculture. While his most-cited papers from 2024 and 2025 are still gaining recognition, they represent foundational steps toward fully autonomous, economically viable underwater inspection. Preece’s research is essential reading for engineers and roboticists aiming to deploy intelligent systems in the challenging offshore environment, bridging the gap between simulation and practical, energy-aware autonomy.
Research Focus
Key Achievements
Top Papers
- 1
- 2