ORCID Profile
0000-0003-2215-5188
Current Organisation
University of Technology Sydney
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In Research Link Australia (RLA), "Research Topics" refer to ANZSRC FOR and SEO codes. These topics are either sourced from ANZSRC FOR and SEO codes listed in researchers' related grants or generated by a large language model (LLM) based on their publications.
Adaptive Agents and Intelligent Robotics | Innovation and Technology Management | Manufacturing Engineering | Manufacturing Robotics and Mechatronics (excl. Automotive Mechatronics) | Control Systems, Robotics and Automation | Artificial Intelligence and Image Processing |
Expanding Knowledge in Engineering | Expanding Knowledge in the Information and Computing Sciences | Expanding Knowledge in Technology | Technological and Organisational Innovation
Publisher: American Institute of Aeronautics and Astronautics (AIAA)
Date: 12-2007
DOI: 10.2514/1.32839
Publisher: IEEE
Date: 05-2011
Publisher: IEEE
Date: 2003
Publisher: IEEE
Date: 05-2013
Publisher: IEEE
Date: 05-2012
Publisher: IEEE
Date: 30-05-2021
Publisher: IEEE
Date: 05-2019
Publisher: IEEE
Date: 05-2009
Publisher: IEEE
Date: 2002
Publisher: Elsevier BV
Date: 07-2014
Publisher: IEEE
Date: 30-05-2021
Publisher: IEEE
Date: 12-2019
Publisher: IEEE
Date: 23-10-2022
Publisher: Robotics: Science and Systems Foundation
Date: 13-07-2015
Publisher: IEEE
Date: 05-2020
Publisher: IEEE
Date: 06-2013
Publisher: IEEE
Date: 10-2018
Publisher: IEEE
Date: 27-09-2021
Publisher: IEEE
Date: 05-2020
Publisher: Springer Science and Business Media LLC
Date: 31-01-2018
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2017
Publisher: Springer Berlin Heidelberg
Date: 2005
DOI: 10.1007/11589990_19
Publisher: Robotics: Science and Systems Foundation
Date: 13-07-2015
Publisher: Elsevier BV
Date: 03-2022
Publisher: IEEE
Date: 30-05-2021
Publisher: IEEE
Date: 05-2020
Publisher: Wiley
Date: 13-01-2016
DOI: 10.1002/ROB.21644
Publisher: Elsevier BV
Date: 11-2023
Publisher: arXiv
Date: 2020
Publisher: IEEE
Date: 23-10-2022
Publisher: IEEE
Date: 05-2020
Publisher: EASD
Date: 2020
Publisher: Springer International Publishing
Date: 03-09-2015
Publisher: arXiv
Date: 2020
Publisher: Springer International Publishing
Date: 2021
Publisher: Springer Berlin Heidelberg
Date: 2013
Publisher: arXiv
Date: 2019
Publisher: IEEE
Date: 23-05-2022
Publisher: arXiv
Date: 2022
Publisher: IEEE
Date: 09-2015
Publisher: Elsevier BV
Date: 12-2023
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2020
Publisher: IEEE
Date: 10-2016
Publisher: ACM
Date: 21-07-2002
Publisher: SAGE Publications
Date: 03-2008
Abstract: Self-reconfiguring robots have the potential to explore highly variable terrain, operating as parallel groups or combining to surmount large obstacles. If the modules are at a smaller scale, they may also be able to physically render arbitrary shapes in an interactive way. In order to realize these capabilities, groups with large numbers of modules must be used, and algorithms to control such large groups must be extremely scalable in order to be executed on simple modules. In this work, we present an algorithm for locomotion of lattice-based self-reconfiguring robots that uses constant memory per module with execution times that are sublinear in the number of modules. The algorithm is inspired by reinforcement learning and uses dynamic programming to plan module paths in parallel. We have also developed a novel localized cooperation scheme that allows the modules to move both without disconnecting the system and with small amounts of communication. The combined algorithm is able to direct locomotion over arbitrary obstacles, and due to continuous replanning the goal can be moved at any time to `joystick' the robot over the environment. The formulation of the goal used in the planning also encourages dynamic stability. We have developed both centralized and decentralized implementations in simulation, as well as an implementation for the Superbot system, and present empirical results showing the sublinear nature of our technique.
Publisher: Unpublished
Date: 2014
Publisher: arXiv
Date: 2016
Publisher: Springer Science and Business Media LLC
Date: 05-03-2009
Publisher: IEEE
Date: 30-05-2021
Publisher: Springer London
Date: 30-09-2011
Publisher: arXiv
Date: 2016
Publisher: IEEE
Date: 20-08-2022
Publisher: MDPI AG
Date: 23-01-2200
DOI: 10.3390/E20020051
Abstract: The Kullback–Leibler (KL) ergence is a fundamental measure of information geometry that is used in a variety of contexts in artificial intelligence. We show that, when system dynamics are given by distributed nonlinear systems, this measure can be decomposed as a function of two information-theoretic measures, transfer entropy and stochastic interaction. More specifically, these measures are applicable when selecting a candidate model for a distributed system, where in idual subsystems are coupled via latent variables and observed through a filter. We represent this model as a directed acyclic graph (DAG) that characterises the unidirectional coupling between subsystems. Standard approaches to structure learning are not applicable in this framework due to the hidden variables however, we can exploit the properties of certain dynamical systems to formulate exact methods based on differential topology. We approach the problem by using reconstruction theorems to derive an analytical expression for the KL ergence of a candidate DAG from the observed dataset. Using this result, we present a scoring function based on transfer entropy to be used as a subroutine in a structure learning algorithm. We then demonstrate its use in recovering the structure of coupled Lorenz and Rössler systems.
Publisher: Wiley
Date: 09-09-2014
DOI: 10.1002/ROB.21536
Publisher: IEEE
Date: 29-05-2023
Publisher: SAGE Publications
Date: 18-09-2016
Abstract: Real-world applications of aerial robots must consider operational constraints such as fuel level during task planning. This paper presents an algorithm for automatically synthesising a continuous non-linear flight controller given a complex temporal logic task specification that can include contingency planning rules. Our method is a hybrid controller where fuel level is treated continuously in the low-level and symbolically in the high-level. The low-level controller assumes the availability of a set of point-estimates of wind velocity and builds a continuous interpolation using Gaussian process regression. Fuel burn and aircraft dynamics are modelled under physically realistic assumptions. Our algorithm is efficient and we show empirically that it is feasible for online execution and replanning. We present several extended simulation ex les of navigation in a wind field and surveillance with fuel constraints, including two different implementations of the low-level controller and also an ex le where the wind field varies over time.
Publisher: Wiley
Date: 22-10-2020
DOI: 10.1002/ROB.21894
Publisher: IEEE
Date: 29-05-2023
Publisher: Springer International Publishing
Date: 21-12-2017
Publisher: Springer Science and Business Media LLC
Date: 19-02-2020
Publisher: arXiv
Date: 2017
Publisher: arXiv
Date: 2017
Publisher: Elsevier BV
Date: 07-2014
Publisher: Springer International Publishing
Date: 2015
Publisher: Springer Science and Business Media LLC
Date: 02-2019
Publisher: The Robotics Society of Japan
Date: 2003
DOI: 10.7210/JRSJ.21.832
Publisher: Frontiers Media SA
Date: 28-11-2016
Publisher: Springer International Publishing
Date: 03-11-2018
Publisher: IEEE
Date: 05-2019
Publisher: Springer Science and Business Media LLC
Date: 04-08-2022
DOI: 10.1038/S41598-022-17120-3
Abstract: Metal hydrides (MH) are known as one of the most suitable material groups for hydrogen energy storage because of their large hydrogen storage capacity, low operating pressure, and high safety. However, their slow hydrogen absorption kinetics significantly decreases storage performance. Faster heat removal from MH storage can play an essential role to enhance its hydrogen absorption rate, resulting in better storage performance. In this regard, the present study aims to improve heat transfer performance to positively impact the hydrogen absorption rate of MH storage systems. A novel semi-cylindrical coil is first designed and optimized for hydrogen storage and embedded as an internal heat exchanger with air as the heat transfer fluid (HTF). The effect of novel heat exchanger configurations is analyzed and compared with normal helical coil geometry, based on various pitch sizes. Furthermore, the operating parameters of MH storage and HTF are numerically investigated to obtain optimal values. ANSYS Fluent 2020 R2 is utilized for the numerical simulations. Results from this study demonstrate that MH storage performance is significantly improved by using a semi-cylindrical coil heat exchanger (SCHE). The hydrogen absorption duration reduces by 59% compared to a normal helical coil heat exchanger. The lowest coil pitch from SCHE leads to a 61% reduction of the absorption time. In terms of operating parameters for the MH storage with SCHE, all selected parameters provide a major improvement in the hydrogen absorption process, especially the inlet temperature of the HTF.
Publisher: Springer International Publishing
Date: 2015
Publisher: IEEE
Date: 05-2018
Publisher: IEEE
Date: 10-2016
Publisher: IEEE
Date: 09-2017
Publisher: IEEE
Date: 24-10-2020
Publisher: Wiley
Date: 22-01-2019
DOI: 10.1111/COBI.13265
Publisher: IEEE
Date: 05-2013
Publisher: IEEE
Date: 10-2012
Publisher: IEEE
Date: 05-2013
Publisher: IEEE
Date: 06-2013
Publisher: Robotics: Science and Systems Foundation
Date: 09-07-2013
Publisher: IEEE
Date: 05-2020
Publisher: Springer International Publishing
Date: 2020
Publisher: Springer International Publishing
Date: 03-09-2015
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2016
Publisher: IEEE
Date: 05-06-2023
Publisher: Wiley
Date: 08-07-2013
DOI: 10.1002/ROB.21471
Publisher: arXiv
Date: 2020
Publisher: Dartmouth College Library Press
Date: 2004
DOI: 10.1349/DDLP.69
Publisher: American Association for the Advancement of Science (AAAS)
Date: 17-10-2018
DOI: 10.1126/SCIROBOTICS.AAT8409
Abstract: Estimation algorithms for wildlife tracking with an autonomous aerial robot are supported by field validation with wild swift parrots.
Publisher: Springer Science and Business Media LLC
Date: 20-02-2017
Publisher: IEEE
Date: 05-2013
Publisher: Springer Science and Business Media LLC
Date: 2020
Publisher: IEEE
Date: 05-2019
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 12-2002
Publisher: IEEE
Date: 04-2007
Publisher: IEEE
Date: 2001
Publisher: IEEE
Date: 2005
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 04-2020
Publisher: Springer Japan
Date: 2007
Publisher: Springer International Publishing
Date: 2020
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 04-2017
Publisher: Springer Science and Business Media LLC
Date: 08-01-2014
Publisher: Elsevier BV
Date: 2018
Publisher: Springer Science and Business Media LLC
Date: 30-10-2015
Publisher: IEEE
Date: 05-2016
Publisher: IEEE
Date: 11-2020
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2017
Publisher: Elsevier BV
Date: 2019
Publisher: IEEE
Date: 05-2012
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2015
Publisher: Springer International Publishing
Date: 2018
Publisher: IEEE
Date: 05-2019
Publisher: IEEE
Date: 29-05-2023
Publisher: IEEE
Date: 05-2012
Publisher: IEEE
Date: 30-05-2021
Publisher: Springer Berlin Heidelberg
Date: 2013
Publisher: Springer Science and Business Media LLC
Date: 13-12-2017
Publisher: arXiv
Date: 2021
Publisher: SAGE Publications
Date: 08-03-2019
Abstract: We propose a decentralized variant of Monte Carlo tree search (MCTS) that is suitable for a variety of tasks in multi-robot active perception. Our algorithm allows each robot to optimize its own actions by maintaining a probability distribution over plans in the joint-action space. Robots periodically communicate a compressed form of their search trees, which are used to update the joint distribution using a distributed optimization approach inspired by variational methods. Our method admits any objective function defined over robot action sequences, assumes intermittent communication, is anytime, and is suitable for online replanning. Our algorithm features a new MCTS tree expansion policy that is designed for our planning scenario. We extend the theoretical analysis of standard MCTS to provide guarantees for convergence rates to the optimal payoff sequence. We evaluate the performance of our method for generalized team orienteering and online active object recognition using real data, and show that it compares favorably to centralized MCTS even with severely degraded communication. These ex les demonstrate the suitability of our algorithm for real-world active perception with multiple robots.
Publisher: International Society for Horticultural Science (ISHS)
Date: 12-2016
Publisher: IEEE
Date: 05-06-2023
Publisher: SAGE Publications
Date: 15-12-2015
Abstract: We are interested in the problem of how to improve estimation in multi-robot information gathering systems by actively controlling the rate of communication between robots. Communication is essential in such systems for decentralized data fusion and decision-making, but wireless networks impose capacity constraints that are frequently overlooked. In order to make efficient use of available capacity, it is necessary to consider a fundamental trade-off between communication cost, computation cost and information value. We introduce a new problem, dynamic information flow, that formalizes this trade-off in terms of decentralized constrained optimization. We propose algorithms that dynamically adjust the data rate of each communication link to maximize an information gain metric subject to constraints on communication and computation resources. The metric is balanced against the communication resources required to transmit data and the computation cost of processing sensor data to form observations. The optimization process selectively routes raw sensor data or processed observation data to zero, one or many robots. Our algorithms therefore allow large systems with many different types of sensors and computational resources to maximize information gain performance while satisfying realistic communication constraints. We also present experimental results with multiple ground robots and multiple sensor types that demonstrate the benefit of dynamic information flow in comparison to simpler bandwidth-limiting methods.
Publisher: IEEE
Date: 05-2018
Publisher: Springer Berlin Heidelberg
Date: 2003
Publisher: ACM
Date: 20-06-2007
Start Date: 04-2014
End Date: 04-2017
Amount: $320,000.00
Funder: Australian Research Council
View Funded ActivityStart Date: 08-2021
End Date: 08-2026
Amount: $4,879,415.00
Funder: Australian Research Council
View Funded Activity