Agricultural Robotics: The Future of Robotic Agriculture
June 18, 2018 Β· Declared Dead Β· π UKRAS White Papers
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Tom Duckett, Simon Pearson, Simon Blackmore, Bruce Grieve, Wen-Hua Chen, Grzegorz Cielniak, Jason Cleaversmith, Jian Dai, Steve Davis, Charles Fox, PΓ₯l From, Ioannis Georgilas, Richie Gill, Iain Gould, Marc Hanheide, Alan Hunter, Fumiya Iida, Lyudmila Mihalyova, Samia Nefti-Meziani, Gerhard Neumann, Paolo Paoletti, Tony Pridmore, Dave Ross, Melvyn Smith, Martin Stoelen, Mark Swainson, Sam Wane, Peter Wilson, Isobel Wright, Guang-Zhong Yang
arXiv ID
1806.06762
Category
cs.RO: Robotics
Citations
283
Venue
UKRAS White Papers
Last Checked
3 months ago
Abstract
Agri-Food is the largest manufacturing sector in the UK. It supports a food chain that generates over Β£108bn p.a., with 3.9m employees in a truly international industry and exports Β£20bn of UK manufactured goods. However, the global food chain is under pressure from population growth, climate change, political pressures affecting migration, population drift from rural to urban regions and the demographics of an aging global population. These challenges are recognised in the UK Industrial Strategy white paper and backed by significant investment via a Wave 2 Industrial Challenge Fund Investment ("Transforming Food Production: from Farm to Fork"). Robotics and Autonomous Systems (RAS) and associated digital technologies are now seen as enablers of this critical food chain transformation. To meet these challenges, this white paper reviews the state of the art in the application of RAS in Agri-Food production and explores research and innovation needs to ensure these technologies reach their full potential and deliver the necessary impacts in the Agri-Food sector.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Robotics
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
AirSim: High-Fidelity Visual and Physical Simulation for Autonomous Vehicles
π
π
The Cartographer
A Survey of Motion Planning and Control Techniques for Self-driving Urban Vehicles
π
π
The Cartographer
Unmanned Aerial Vehicles: A Survey on Civil Applications and Key Research Challenges
π
π
The Cartographer
A Survey of Autonomous Driving: Common Practices and Emerging Technologies
R.I.P.
π»
Ghosted
Learning agile and dynamic motor skills for legged robots
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted