Watching Grass Grow: Long-term Visual Navigation and Mission Planning for Autonomous Biodiversity Monitoring
<|reference_start|>Watching Grass Grow: Long-term Visual Navigation and Mission Planning for Autonomous Biodiversity Monitoring: We describe a challenging robotics deployment in a complex ecosystem to monitor a rich plant community. The study site is dominated by dynamic grassland vegetation and is thus visually ambiguous and liable to drastic appearance change over the course of a day and especially through the growing season. This dynamism and complexity in appearance seriously impact the stability of the robotics platform, as localisation is a foundational part of that control loop, and so routes must be carefully taught and retaught until autonomy is robust and repeatable. Our system is demonstrated over a 6-week period monitoring the response of grass species to experimental climate change manipulations. We also discuss the applicability of our pipeline to monitor biodiversity in other complex natural settings.<|reference_end|>
@article{gadd2024watching,
    title={Watching Grass Grow: Long-term Visual Navigation and Mission Planning
  for Autonomous Biodiversity Monitoring},
    author={Matthew Gadd, Daniele De Martini, Luke Pitt, Wayne Tubby, Matthew
  Towlson, Chris Prahacs, Oliver Bartlett, John Jackson, Man Qi, Paul Newman,
  Andrew Hector, Roberto Salguero-G'omez, Nick Hawes},
    journal={arXiv preprint arXiv:2404.10446},
    year={2024},
    archivePrefix={arXiv},
    eprint={2404.10446},
    primaryClass={cs.RO}
}