41 citations · 65 across the 14 of their papers we have counts for
14 papers
Droneulator: A Portable UAV Simulator for Agricultural Workflows with RotorPy and Godot 4
Jacob Swindell, Michael Lowen, Marija Popovic +1
Agricultural UAV research requires simulators that integrate realistic 3D scenes, high-fidelity vehicle dynamics, and robotics middleware, while remaining practical to deploy acros…
Semantic Landmark Particle Filter for Robot Localisation in Vineyards
Rajitha de Silva, Jonathan Cox, James R. Heselden +3
Reliable localisation in vineyards is hindered by row-level perceptual aliasing: parallel crop rows produce nearly identical LiDAR observations, causing geometry-only and vision-ba…
Perception-Aware Autonomous Exploration in Feature-Limited Environments
Moji Shi, Rajitha de Silva, Hang Yu +2
Autonomous exploration in unknown environments typically relies on onboard state estimation for localisation and mapping. Existing exploration methods primarily maximise coverage e…
Active Informative Planning for UAV-based Weed Mapping using Discrete Gaussian Process Representations
Jacob Swindell, Marija Popović, Riccardo Polvara
Accurate agricultural weed mapping using unmanned aerial vehicles (UAVs) is crucial for precision farming. While traditional methods rely on rigid, pre-defined flight paths and int…
Semantic-Aware Particle Filter for Reliable Vineyard Robot Localisation
Rajitha de Silva, Jonathan Cox, James R. Heselden +3
Accurate localisation is critical for mobile robots in structured outdoor environments, yet LiDAR-based methods often fail in vineyards due to repetitive row geometry and perceptua…
Keypoint Semantic Integration for Improved Feature Matching in Outdoor Agricultural Environments
Rajitha de Silva, Jonathan Cox, Marija Popovic +3
Robust robot navigation in outdoor environments requires accurate perception systems capable of handling visual challenges such as repetitive structures and changing appearances. V…
Discrete Gaussian Process Representations for Optimising UAV-based Precision Weed Mapping
Jacob Swindell, Madeleine Darbyshire, Marija Popovic +1
Accurate agricultural weed mapping using UAVs is crucial for precision farming applications. Traditional methods rely on orthomosaic stitching from rigid flight paths, which is com…
LTS-NET: End-to-end Unsupervised Learning of Long-Term 3D Stable objects
Ibrahim Hroob, Sergi Molina, Riccardo Polvara +2
In this research, we present an end-to-end data-driven pipeline for determining the long-term stability status of objects within a given environment, specifically distinguishing be…
Collection and Evaluation of a Long-Term 4D Agri-Robotic Dataset
Riccardo Polvara, Sergi Molina Mellado, Ibrahim Hroob +2
Long-term autonomy is one of the most demanded capabilities looked into a robot. The possibility to perform the same task over and over on a long temporal horizon, offering a high…
Benchmark of visual and 3D lidar SLAM systems in simulation environment for vineyards
Ibrahim Hroob, Riccardo Polvara, Sergi Molina +2
In this work, we present a comparative analysis of the trajectories estimated from various Simultaneous Localization and Mapping (SLAM) systems in a simulation environment for vine…
Navigate-and-Seek: a Robotics Framework for People Localization in Agricultural Environments
Riccardo Polvara, Francesco Del Duchetto, Gerhard Neumann +1
The agricultural domain offers a working environment where many human laborers are nowadays employed to maintain or harvest crops, with huge potential for productivity gains throug…
A Next-Best-Smell Approach for Remote Gas Detection with a Mobile Robot
Riccardo Polvara, Marco Trabattoni, Tomasz Piotr Kucner +3
The problem of gas detection is relevant to many real-world applications, such as leak detection in industrial settings and landfill monitoring. Using mobile robots for gas detecti…
Autonomous Quadrotor Landing using Deep Reinforcement Learning
Riccardo Polvara, Massimiliano Patacchiola, Sanjay Sharma +4
Landing an unmanned aerial vehicle (UAV) on a ground marker is an open problem despite the effort of the research community. Previous attempts mostly focused on the analysis of han…
Monocular Visual Odometry for an Unmanned Sea-Surface Vehicle
George Terzakis, Riccardo Polvara, Sanjay Sharma +2
We tackle the problem of localizing an autonomous sea-surface vehicle in river estuarine areas using monocular camera and angular velocity input from an inertial sensor. Our method…