Tree Hugger is an environmental monitoring robot designed and built independently by Suhandan Thangadurai, a 15-year-old student from Fife. It uses AI vision, thermal imaging, soil nutrient sensing, and centimetre-level GPS to detect early signs of tree stress and disease before symptoms are visible.

Watch a video of the robot here.

Whilst the grant panel acknowledged potential usability concerns, they were interested in how the work will develop and wanted to commend the development work that’s already taken place. The current prototype is remotely piloted; this project will add genuine autonomous navigation, so the robot can travel to a set of known, GPS-logged tree locations on its own, avoiding obstacles along the way using LiDAR-based mapping, to carry out its full sensor assessment at each site without a human operator present. Autonomous revisiting turns a one-off demonstration into a repeatable monitoring tool.

The work will take place in a defined test woodland area in Fife, where an earlier prototype version has already been field-tested. The robot will be further developed, building on an existing, working sensor and communications architecture validated across multiple prior iterations, and integrating new navigation hardware (LiDAR, dedicated onboard compute) into the existing, proven chassis rather than starting over.