Publication details for Professor Toby BreckonMaciel-Pearson, B.G. & Breckon, T.P. (2017), An Optimised Deep Neural Network Approach for Forest Trail Navigation for UAV Operation within the Forest Canopy, The UK-RAS Network Conference on Robotics and Autonomous Systems: robots working for and among us. Bristol, UK Robotics and Autonomous Systems Network, 19-23.
- Publication type: Conference Paper
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Author(s) from Durham
Autonomous flight within a forest canopy represents a key challenge for generalised scene understanding
on-board a future Unmanned Aerial Vehicle (UAV) platform. Here we present an approach for automatic
trail navigation within such an environment that successfully generalises across differing image resolutions -
allowing UAV with varying sensor payload capabilities to operate equally in such challenging environmental
conditions. Specifically, this work presents an optimised deep neural network architecture, capable of stateof-the-art
performance across varying resolution aerial UAV imagery, that improves forest trail detection for
UAV guidance even when using significantly low resolution images that are representative of low-cost search
and rescue capable UAV platforms.