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  SCENARIO: A Robotic Ecologist for Automated Habitat Monitoring


   School of Mechanical Engineering Sciences

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  Dr Robert Siddall, Dr Ana Andries, Prof S Morse, Prof R Murphy  No more applications being accepted  Competition Funded PhD Project (Students Worldwide)

About the Project

Global biodiversity loss creates an urgent need to change the way the built environment interacts with the natural world, and new solutions are required for understanding nature. Earth observation satellites offer the means to map and analyse macroecological trends, but to be truly effective, this must be paired with ground-based data, which is resource and manpower intensive to collect. However, recent advances in robotics now makes it possible to automate tasks in complex outdoor environments. Robotic data collection on the ground offers a way to collect dense data at larger volumes than it is possible for humans to collect, and unlike aerial and space-based sensing, ground vehicles benefit from long operating times and the ability to distinguish microhabitats beneath the tree canopy.

However, before robotic monitoring can become widely used, experienced scientists must test and refine approaches and hardware: This project will deploy a ‘robotic ecologist’ recently developed at the University of Surrey, and use it to demonstrate ecosystem surveying of habitats using advanced sensors, and pair the observations directly with high-resolution satellite data. The project’s student will be responsible for integrating sensors and enhancing the robot to tackle progressively more challenging field sites. Through extensive robotic fieldwork, the student will gain experience in both modern robotics engineering and environmental science and become a leader in the use of mobile robots in service of conservation and sustainability goals.

Training Opportunities

The student will have the opportunity to deploy robotic systems in the field, gaining simultaneous experience in fieldwork and engineering, supported by experienced roboticists and become comfortable with the rapid build-test cycle found in modern robotics. The student will have the opportunity to conduct extensive field work with partners, and will have the option of interning with external institutions involved in forest science / ecology.

Student Profile

This project would be best suited to a student having a background in mechanical, electrical or aerospace engineering, with an interest in robotics and environmental science. Applicants should hold or expect to gain a minimum of a 2:1 Bachelor Degree, Masters Degree with Merit, or equivalent. We will also consider candidates with different academic paths but with experience acquired from a research position, or equivalent, that is relevant to the topic of the PhD project.

The project involves robotics and data analysis, but also entails significant field work so enthusiasm for work outdoors, and a willingness to get muddy will be helpful.

 Knowledge of image analysis and geospatial information systems would be an asset.

Experience with Python or C++ would be advantageous but not required, as would any practical experience with mobile robotics.

 A candidate with a strong desire to improve the natural world would find the project rewarding.

To apply, please follow the instructions at https://research.reading.ac.uk/scenario/apply/

Agriculture (1) Computer Science (8) Engineering (12) Environmental Sciences (13) Geography (17)

Funding Notes

This project is potentially funded by the Scenario NERC Doctoral Training Partnership, subject to a competition to identify the strongest applicants.
Due to UKRI rules, the DTP can only fund a very limited number of international students. We will only consider applications from international students with an outstanding academic background placing them in the top 10% of their cohort.
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