Salah Sukkarieh
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View article: Multi-Robot Systems for Collective Sampling
Multi-Robot Systems for Collective Sampling Open
Field sampling is a critical task in applications such as environmental monitoring and precision agriculture. Efficiently completing these tasks while maintaining robots' tilt stability is particularly challenging when multiple robots are …
View article: A Framework to Enable Eco‐Cyber‐Physical Systems for Robotics‐Focused Digital Twins in Smart Farming
A Framework to Enable Eco‐Cyber‐Physical Systems for Robotics‐Focused Digital Twins in Smart Farming Open
This paper introduces the R‐ECPS (Robotics‐focused Eco‐Cyber‐Physical System) framework for the development of robotics‐enabled digital twins, integrating human knowledge into the decision‐making process. Our framework adapts ECPS and Digi…
View article: Automated Testing of Spatially-Dependent Environmental Hypotheses through Active Transfer Learning
Automated Testing of Spatially-Dependent Environmental Hypotheses through Active Transfer Learning Open
The efficient collection of samples is an important factor in outdoor information gathering applications on account of high sampling costs such as time, energy, and potential destruction to the environment. Utilization of available a-prior…
View article: Length Modelling of Spiral Superficial Soft Strain Sensors Using Geodesics and Covering Spaces
Length Modelling of Spiral Superficial Soft Strain Sensors Using Geodesics and Covering Spaces Open
Piecewise constant curvature soft actuators can generate various types of movements. These actuators can undergo extension, bending, rotation, twist, or a combination of these. Proprioceptive sensing provides the ability to track their mov…
View article: Identifiability Analysis of Noise Covariances for LTI Stochastic Systems with Unknown Inputs
Identifiability Analysis of Noise Covariances for LTI Stochastic Systems with Unknown Inputs Open
Most existing works on optimal filtering of linear time-invariant (LTI) stochastic systems with arbitrary unknown inputs assume perfect knowledge of the covariances of the noises in the filter design. This is impractical and raises the que…
View article: Manipulating UAV Imagery for Satellite Model Training, Calibration and Testing
Manipulating UAV Imagery for Satellite Model Training, Calibration and Testing Open
Modern livestock farming is increasingly data driven and frequently relies on efficient remote sensing to gather data over wide areas. High resolution satellite imagery is one such data source, which is becoming more accessible for farmers…
View article: Resource and Response Aware Path Planning for Long-Term Autonomy of Ground Robots in Agriculture
Resource and Response Aware Path Planning for Long-Term Autonomy of Ground Robots in Agriculture Open
Achieving long-term autonomy for mobile robots operating in real-world, unstructured environments, such as farms, remains a significant challenge. Such tasks are made increasingly complex when undertaken in the presence of moving humans or…
View article: One-Shot Learning with Pseudo-Labeling for Cattle Video Segmentation in Smart Livestock Farming
One-Shot Learning with Pseudo-Labeling for Cattle Video Segmentation in Smart Livestock Farming Open
Computer vision-based technologies play a key role in precision livestock farming, and video-based analysis approaches have been advocated as useful tools for automatic animal monitoring, behavior analysis, and efficient welfare measuremen…
View article: The Noise Covariances of Linear Gaussian Systems with Unknown Inputs Are Not Uniquely Identifiable Using Autocovariance Least-squares
The Noise Covariances of Linear Gaussian Systems with Unknown Inputs Are Not Uniquely Identifiable Using Autocovariance Least-squares Open
Existing works in optimal filtering for linear Gaussian systems with arbitrary unknown inputs assume perfect knowledge of the noise covariances in the filter design. This is impractical and raises the question of whether and under what con…
View article: Automated Individual Cattle Identification Using Video Data: A Unified Deep Learning Architecture Approach
Automated Individual Cattle Identification Using Video Data: A Unified Deep Learning Architecture Approach Open
Individual cattle identification is a prerequisite and foundation for precision livestock farming. Existing methods for cattle identification require radio frequency or visual ear tags, all of which are prone to loss or damage. Here, we pr…
View article: Intelligent Perception-Based Cattle Lameness Detection and Behaviour Recognition: A Review
Intelligent Perception-Based Cattle Lameness Detection and Behaviour Recognition: A Review Open
The growing world population has increased the demand for animal-sourced protein. However, animal farming productivity is faced with challenges from traditional farming practices, socioeconomic status, and climate change. In recent years, …
View article: One-Shot Learning-Based Animal Video Segmentation
One-Shot Learning-Based Animal Video Segmentation Open
Deep learning-based video segmentation methods can offer a good performance after being trained on the large-scale pixel labeled datasets. However, a pixel-wise manual labeling of animal images is challenging and time consuming due to irre…
View article: Active Information Acquisition under Arbitrary Unknown Disturbances
Active Information Acquisition under Arbitrary Unknown Disturbances Open
Trajectory optimization of sensing robots to actively gather information of targets has received much attention in the past. It is well-known that under the assumption of linear Gaussian target dynamics and sensor models the stochastic Act…
View article: Resource and Response Aware Path Planning for Long-term Autonomy of Ground Robots in Agriculture
Resource and Response Aware Path Planning for Long-term Autonomy of Ground Robots in Agriculture Open
Achieving long-term autonomy for mobile robots operating in real-world unstructured environments such as farms remains a significant challenge. This is made increasingly complex in the presence of moving humans or livestock. These environm…
View article: Dataset and Performance Comparison of Deep Learning Architectures for Plum Detection and Robotic Harvesting
Dataset and Performance Comparison of Deep Learning Architectures for Plum Detection and Robotic Harvesting Open
Many automated operations in agriculture, such as weeding and plant counting, require robust and accurate object detectors. Robotic fruit harvesting is one of these, and is an important technology to address the increasing labour shortages…
View article: A Hierarchical Framework for Long-term and Robust Deployment of Field Ground Robots in Large-Scale Farming
A Hierarchical Framework for Long-term and Robust Deployment of Field Ground Robots in Large-Scale Farming Open
Achieving long term autonomy of robots operating in dynamic environments such as farms remains a significant challenge. Arguably, the most demanding factors to achieve this are the on-board resource constraints such as energy, planning in …
View article: Design and Evaluation of a Modular Robotic Plum Harvesting System Utilising Soft Components
Design and Evaluation of a Modular Robotic Plum Harvesting System Utilising Soft Components Open
The human labour required for tree crop harvesting is a major cost component in fruit production and is increasing. To address this, many existing research works have sought to demonstrate commercially viable robotic harvesting for tree cr…
View article: Path Planning in Dynamic Environments using Generative RNNs and Monte Carlo Tree Search
Path Planning in Dynamic Environments using Generative RNNs and Monte Carlo Tree Search Open
State of the art methods for robotic path planning in dynamic environments, such as crowds or traffic, rely on hand crafted motion models for agents. These models often do not reflect interactions of agents in real world scenarios. To over…
View article: Using energy requirements to compare the suitability of alternative methods for broadcast and site-specific weed control – CORRIGENDUM
Using energy requirements to compare the suitability of alternative methods for broadcast and site-specific weed control – CORRIGENDUM Open
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View article: The future of agricultural technologies
The future of agricultural technologies Open
Australian agriculture is world-renowned for leadership in harvesting practices, water-efficient agronomy, crop and livestock breeding, conservation tillage and development of fit-for-purpose farm machinery. While Australia exports two-thi…
View article: Predicting Responses to a Robot's Future Motion using Generative Recurrent Neural Networks
Predicting Responses to a Robot's Future Motion using Generative Recurrent Neural Networks Open
Robotic navigation through crowds or herds requires the ability to both predict the future motion of nearby individuals and understand how these predictions might change in response to a robot's future action. State of the art trajectory p…
View article: Using energy requirements to compare the suitability of alternative methods for broadcast and site-specific weed control
Using energy requirements to compare the suitability of alternative methods for broadcast and site-specific weed control Open
The widespread use of herbicides in cropping systems has led to the evolution of resistance in major weeds. The resultant loss of herbicide efficacy is compounded by a lack of new herbicide sites of action, driving demand for alternative w…
View article: Receding horizon estimation and control with structured noise blocking for mobile robot slip compensation
Receding horizon estimation and control with structured noise blocking for mobile robot slip compensation Open
The control of field robots in varying and uncertain terrain conditions presents a challenge for autonomous navigation. Online estimation of the wheel-terrain slip characteristics is essential for generating the accurate control prediction…
View article: Ladybird Cobbitty 2017 Brassica Dataset
Ladybird Cobbitty 2017 Brassica Dataset Open
This data set contains weekly scans of cauliflower and broccoli covering a ten week growth cycle from transplant to harvest. The data set includes ground-truth, physical characteristics of the crop; environmental data collected by a weathe…