Ben Hollings
Papers
1
Total Citations
12
H-Index
1
About
Ben Hollings is a researcher at the forefront of autonomous underwater robotics, with a primary focus on active perception and energy-efficient environmental monitoring. His most cited work, "Active perception for plume source localisation with underwater gliders" (2018), introduces a novel Gaussian process regression technique that enables underwater gliders to intelligently localise unknown chemical or thermal plume sources while minimising energy consumption. This contribution addresses a critical challenge in marine robotics: how to perform persistent, autonomous search missions in vast and dynamic ocean environments. With 12 citations, this paper has laid foundational groundwork for integrating probabilistic machine learning with low-power robotic platforms. Hollings’ research sits at the intersection of field robotics, Bayesian inference, and marine science, offering practical solutions for pollution tracking, hydrothermal vent discovery, and underwater search-and-rescue. His work is particularly notable for bridging theoretical active perception frameworks with real-world hardware constraints, making autonomous ocean exploration more viable and sustainable. For students and researchers, Hollings exemplifies how principled algorithmic design can unlock new capabilities in environmental robotics.
Research Focus
Key Achievements
Top Papers
- 1Active perception for plume source localisation with underwater gliders12 citations · 2018