99 citations · 258 across the 17 of their papers we have counts for
19 papers
Cooperating with Future Collaborators: Multi-Agent RL under Staggered Participation
Jianglin Qiao, Siyi Hu, Thien Hoang Nguyen +2
In cooperative Multi-Agent Reinforcement Learning (MARL), agents are often trained under concurrent participation, while in many tasks some agents act earlier and leave task-releva…
Identifiability Analysis of Noise Covariances for LTI Stochastic Systems with Unknown Inputs
He Kong, Salah Sukkarieh, Travis J. Arnold +3
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 i…
Manipulating UAV Imagery for Satellite Model Training, Calibration and Testing
Jasper Brown, Cameron Clark, Sabrina Lomax +2
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…
The Noise Covariances of Linear Gaussian Systems with Unknown Inputs Are Not Uniquely Identifiable Using Autocovariance Least-squares
He Kong, Salah Sukkarieh, Travis J. Arnold +2
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 imprac…
Automated Aerial Animal Detection When Spatial Resolution Conditions Are Varied
Jasper Brown, Yongliang Qiao, Cameron Clark +3
Knowing where livestock are located enables optimized management and mustering. However, Australian farms are large meaning that many of Australia's livestock are unmonitored which…
Active Information Acquisition under Arbitrary Unknown Disturbances
Jennifer Wakulicz, He Kong, Salah Sukkarieh
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 Ga…
Experimental Evaluation of a Hierarchical Operating Framework for Ground Robots in Agriculture
Stuart Eiffert, Nathan D. Wallace, He Kong +2
For mobile robots to be effectively applied to real world unstructured environments -- such as large scale farming -- they require the ability to generate adaptive plans that accou…
Resource and Response Aware Path Planning for Long-term Autonomy of Ground Robots in Agriculture
Stuart Eiffert, Nathan D. Wallace, He Kong +2
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…
Dataset and Performance Comparison of Deep Learning Architectures for Plum Detection and Robotic Harvesting
Jasper Brown, Salah Sukkarieh
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 impo…
Design and Evaluation of a Modular Robotic Plum Harvesting System Utilising Soft Components
Jasper Brown, Salah Sukkarieh
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 dem…
Probabilistic Crowd GAN: Multimodal Pedestrian Trajectory Prediction using a Graph Vehicle-Pedestrian Attention Network
Stuart Eiffert, Kunming Li, Mao Shan +3
Understanding and predicting the intention of pedestrians is essential to enable autonomous vehicles and mobile robots to navigate crowds. This problem becomes increasingly complex…
A Hierarchical Framework for Long-term and Robust Deployment of Field Ground Robots in Large-Scale Farming
Stuart Eiffert, Nathan D. Wallace, He Kong +2
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…
A Multi-Core Fibre Photonic Lantern Based Spectrograph for Raman Spectroscopy
Christopher H. Betters, Joss Bland-Hawthorn, Salah Sukkarieh +2
We report on the development of a compact (volume 100\:cm), multimode diffraction-limited Raman spectrograph and probe designed to be compact as possible. The spectro…
Path Planning in Dynamic Environments using Generative RNNs and Monte Carlo Tree Search
Stuart Eiffert, He Kong, Navid Pirmarzdashti +1
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 refl…
Predicting Responses to a Robot's Future Motion using Generative Recurrent Neural Networks
Stuart Eiffert, Salah Sukkarieh
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 respons…
Receding horizon estimation and control with structured noise blocking for mobile robot slip compensation
Nathan Wallace, He Kong, Andrew Hill +1
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…
Metamorphic Moving Horizon Estimation
He Kong, Salah Sukkarieh
This paper considers a practical scenario where a classical estimation method might have already been implemented on a certain platform when one tries to apply more advanced techni…
Multi-Modal Active Perception for Information Gathering in Science Missions
Akash Arora, P. Michael Furlong, Robert Fitch +2
Robotic science missions in remote environments, such as deep ocean and outer space, can involve studying phenomena that cannot directly be observed using on-board sensors but must…
An Approach to Autonomous Science by Modeling Geological Knowledge in a Bayesian Framework
Akash Arora, Robert Fitch, Salah Sukkarieh
Autonomous Science is a field of study which aims to extend the autonomy of exploration robots from low level functionality, such as on-board perception and obstacle avoidance, to…