197 citations · 398 across the 13 of their papers we have counts for
7 papers · 1 filter
Kriging-Based Robotic Exploration for Soil Moisture Mapping Using a Cosmic-Ray Sensor
Jaime Pulido Fentanes, Amir Badiee, Tom Duckett +3
Soil moisture monitoring is a fundamental process to enhance agricultural outcomes and to protect the environment. The traditional methods for measuring moisture content in soil ar…
Warped Hypertime Representations for Long-term Autonomy of Mobile Robots
Tomas Krajnik, Tomas Vintr, Sergi Molina +3
This paper presents a novel method for introducing time into discrete and continuous spatial representations used in mobile robotics, by modelling long-term, pseudo-periodic variat…
Agricultural Robotics: The Future of Robotic Agriculture
Tom Duckett, Simon Pearson, Simon Blackmore +27
Agri-Food is the largest manufacturing sector in the UK. It supports a food chain that generates over £108bn p.a., with 3.9m employees in a truly international industry and exports…
Recurrent-OctoMap: Learning State-based Map Refinement for Long-Term Semantic Mapping with 3D-Lidar Data
Li Sun, Zhi Yan, Anestis Zaganidis +2
This paper presents a novel semantic mapping approach, Recurrent-OctoMap, learned from long-term 3D Lidar data. Most existing semantic mapping approaches focus on improving semanti…
Artificial Intelligence for Long-Term Robot Autonomy: A Survey
Lars Kunze, Nick Hawes, Tom Duckett +2
Autonomous systems will play an essential role in many applications across diverse domains including space, marine, air, field, road, and service robotics. They will assist us in o…
3D Soil Compaction Mapping through Kriging-based Exploration with a Mobile Robot
Jaime Pulido Fentanes, Iain Gould, Tom Duckett +2
This paper presents an automated method for creating spatial maps of soil condition with an outdoor mobile robot. Effective soil mapping on farms can enhance yields, reduce inputs…
Learning monocular visual odometry with dense 3D mapping from dense 3D flow
Cheng Zhao, Li Sun, Pulak Purkait +2
This paper introduces a fully deep learning approach to monocular SLAM, which can perform simultaneous localization using a neural network for learning visual odometry (L-VO) and d…