Explanipedia

Long-term mobile robot localization in dynamic environments using spectral maps Open

Tomáš Krajník, Jaime Pulido Fentanes, Óscar Martínez Mozos, Johan Ekekrantz, Marc Hanheide , et al. · 2024

The video presents a novel approach for vision-based topological localisation in dynamic indoor environments. In contrast to other approaches that rely on static image features, our method explicitly models the temporal dynamics of the vis…

The ILIAD Safety Stack: Human-Aware Infrastructure-Free Navigation of Industrial Mobile Robots Open

Sergi Molina, Anna Mannucci, Martin Magnusson, Daniel Adolfsson, Henrik Andreasson , et al. · 2023

Safe yet efficient operation of professional service robots within logistics or production in human-robot shared environments requires a flexible human-aware navigation stack. In this manuscript, we propose the ILIAD safety stack comprisin…

Towards Long-term Autonomy: A Perspective from Robot Learning Open

Zhi Yan, Sun Li, Tomáš Krajník, Tom Duckett, Nicola Bellotto · 2022

In the future, service robots are expected to be able to operate autonomously for long periods of time without human intervention. Many work striving for this goal have been emerging with the development of robotics, both hardware and soft…

NDT-Transformer: Large-Scale 3D Point Cloud Localisation using the Normal Distribution Transform Representation Open

Zhicheng Zhou, Cheng Zhao, Daniel Adolfsson, Songzhi Su, Yang Gao , et al. · 2021

3D point cloud-based place recognition is highly demanded by autonomous driving in GPS-challenged environments and serves as an essential component (i.e. loop-closure detection) in lidar-based SLAM systems. This paper proposes a novel appr…

Real-time detection of broccoli crops in 3D point clouds for autonomous robotic harvesting Open

Hector A. Montes, Justin Le Louëdec, Grzegorz Cielniak, Tom Duckett · 2020

Real-time 3D perception of the environment is crucial for the adoption and deployment of reliable autonomous harvesting robots in agriculture. Using data collected with RGB-D cameras under farm field conditions, we present two methods for …

Estimating soil aggregate size distribution from images using pattern spectra Open

Petra Bosilj, Iain Gould, Tom Duckett, Grzegorz Cielniak · 2020

Robot perception of static and dynamic objects with an autonomous floor scrubber Open

Zhi Yan, Simon Schreiberhuber, Georg Halmetschlager-Funek, Tom Duckett, Markus Vincze , et al. · 2020

Segmentation and detection from organised 3D point clouds: a case study in broccoli head detection Open

Justin Le Louëdec, Hector A. Montes, Tom Duckett, Grzegorz Cielniak · 2020

Autonomous harvesting is becoming an important challenge and necessity in agriculture, because of the lack of labour and the growth of population needing to be fed. Perception is a key aspect of autonomous harvesting and is very challengin…

Towards bio-inspired fruit detection for agriculture Open

Zeke Hobbs, Tom Duckett, Simon Pearson, Michael Mangan · 2020

Localising Faster: Efficient and precise lidar-based robot localisation in large-scale environments Open

Li Sun, Daniel Adolfsson, Martin Magnusson, Henrik Andreasson, Ingmar Posner , et al. · 2020

This paper proposes a novel approach for global localisation of mobile robots in large-scale environments. Our method leverages learning-based localisation and filtering-based localisation, to localise the robot efficiently and precisely t…

Robot Perception of Static and Dynamic Objects with an Autonomous Floor Scrubber Open

Zhi Yan, Simon Schreiberhuber, Georg Halmetschlager-Funek, Tom Duckett, Markus Vincze , et al. · 2020

This paper presents the perception system of a new professional cleaning robot for large public places. The proposed system is based on multiple sensors including 3D and 2D lidar, two RGB-D cameras and a stereo camera. The two lidars toget…

Semantically Assisted Loop Closure in SLAM Using NDT Histograms Open

Anestis Zaganidis, Alexandros Zerntev, Tom Duckett, Grzegorz Cielniak · 2019

Precise knowledge of pose is of great importance for reliable operation of mobile robots in outdoor environments. Simultaneous localization and mapping (SLAM) is the online construction of a map during exploration of an environment. One of…

Kriging‐based robotic exploration for soil moisture mapping using a cosmic‐ray sensor Open

Jaime Pulido Fentanes, Amir Badiee, Tom Duckett, Jonathan Evans, Simon Pearson , et al. · 2019

Soil moisture monitoring is a fundamental process to enhance agricultural outcomes and to protect the environment. The traditional methods for measuring moisture content in the soil are laborious and expensive, and therefore there is a gro…

Warped Hypertime Representations for Long-Term Autonomy of Mobile Robots Open

Tomáš Krajník, Tomáš Vintr, Sergi Molina, Jaime Pulido Fentanes, Grzegorz Cielniak , et al. · 2019

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 variations caused by human activities. Unlike previous approaches…

The challenges posed by global broadacre crops in delivering smart agri-robotic solutions: A fundamental rethink is required Open

Bruce Grieve, Tom Duckett, Martin Collison, Lesley A. Boyd, Jonathan West , et al. · 2019

Spatio-temporal representation for long-term anticipation of human presence in service robotics Open

Tomáš Vintr, Zhi Yan, Tom Duckett, Tomáš Krajník · 2019

We propose an efficient spatio-temporal model for mobile autonomous robots operating in human populated \nenvironments. Our method aims to model periodic temporal patterns of people presence, which are based on peoples’ \nroutines and habi…

Go with the Flow: Exploration and Mapping of Pedestrian Flow Patterns from Partial Observations Open

Sergi Molina, Grzegorz Cielniak, Tom Duckett · 2019

Understanding how people are likely to behave in an environment is a key requirement for efficient and safe robot navigation. However, mobile platforms are subject to spatial and temporal constraints, meaning that only partial observations…

Model based 3D point cloud segmentation for automated selective broccoli harvesting* Open

Hector A. Montes, Grzegorz Cielniak, Tom Duckett · 2019

Segmentation of 3D objects in cluttered scenes is a highly relevant problem. Given a 3D point cloud produced by a depth sensor, the goal is to separate objects of interest in the foreground from other elements in the background. We researc…

Kriging-Based Robotic Exploration for Soil Moisture Mapping Using a\n Cosmic-Ray Sensor Open

Jaime Pulido Fentanes, Amir Badiee, Tom Duckett, Jonathan Evans, Simon Pearson , et al. · 2018

Soil moisture monitoring is a fundamental process to enhance agricultural\noutcomes and to protect the environment. The traditional methods for measuring\nmoisture content in soil are laborious and expensive, and therefore there is a\ngrow…

Dense RGB-D Semantic Mapping with Pixel-Voxel Neural Network Open

Cheng Zhao, Li Sun, Pulak Purkait, Tom Duckett, Rustam Stolkin · 2018

In this paper, a novel Pixel-Voxel network is proposed for dense 3D semantic mapping, which can perform dense 3D mapping while simultaneously recognizing and labelling the semantic category each point in the 3D map. In our approach, we ful…

Artificial Intelligence for Long-Term Robot Autonomy: A Survey Open

Lars Kunze, Nick Hawes, Tom Duckett, Marc Hanheide, Tomáš Krajník · 2018

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 our daily routines and perform dangerous, dirty and dull tas…

Recurrent-OctoMap: Learning State-based Map Refinement for Long-Term Semantic Mapping with 3D-Lidar Data Open

Li Sun, Zhi Yan, Anestis Zaganidis, Cheng Zhao, Tom Duckett · 2018

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 semantic understanding of single frames, rather than 3D refinement…

Agricultural Robotics: The Future of Robotic Agriculture Open

Tom Duckett, Simon Pearson, Simon Blackmore, Bruce Grieve · 2018

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 £20bn of UK manufactured goods. However, the global food c…

3-D Soil Compaction Mapping Through Kriging-Based Exploration With a Mobile Robot Open

Jaime Pulido Fentanes, Iain Gould, Tom Duckett, Simon Pearson, Grzegorz Cielniak · 2018

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 and help protect the environment. Traditionally, data are c…

White paper - Agricultural Robotics: The Future of Robotic Agriculture Open

Tom Duckett, Simon Pearson, Simon Blackmore, Bruce Grieve, Melvyn Smith · 2018

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 £20bn of UK manufactured goods. However, the global food c…

Agricultural Robotics: The Future of Robotic Agriculture Open

Tom Duckett, Simon Pearson, Simon Blackmore, Bruce Grieve, Wen‐Hua Chen , et al. · 2018

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 £20bn of UK manufactured goods. However, the global food c…

Connected attribute morphology for unified vegetation segmentation and classification in precision agriculture Open

Petra Bosilj, Tom Duckett, Grzegorz Cielniak · 2018

3D Soil Compaction Mapping through Kriging-based Exploration with a\n Mobile Robot Open

Jaime Pulido Fentanes, Iain Gould, Tom Duckett, Simon Pearson, Grzegorz Cielniak · 2018

This paper presents an automated method for creating spatial maps of soil\ncondition with an outdoor mobile robot. Effective soil mapping on farms can\nenhance yields, reduce inputs and help protect the environment. Traditionally,\ndata ar…

Learning monocular visual odometry with dense 3D mapping from dense 3D flow Open

Cheng Zhao, Li Sun, Pulak Purkait, Tom Duckett, Rustam Stolkin · 2018

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 dense 3D mapping. Dense 2D flow and a depth image are genera…

Multisensor Online Transfer Learning for 3D LiDAR-based Human Classification with a Mobile Robot Open

Zhi Yan, Li Sun, Tom Duckett, Nicola Bellotto · 2018

Human detection and tracking is an essential task for service robots, where the combined use of multiple sensors has potential advantages that are yet to be exploited. In this paper, we introduce a framework allowing a robot to learn a new…

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