Academic Research

Hello. I’m focused on designing better information systems for safety critical systems. I work within the Robotics Institute (RI) at the University of Technology Sydney as a research fellow.

Multi-Robot Exploration with Inferred Human Intent in Large-Scale Field Experiments

Late-Breaking Results Poster Session, Australasian Conference on Robotics & Automation (ACRA), 2024

We present a multi-robot system (MRS) designed to support humans in hazardous environments through predictive exploration. Using Human Intent Inference (HII) and Decentralised Monte Carlo Tree Search (Dec-MCTS), our MRS prioritises areas relevant to humans. Late-breaking simulation and hardware results support our 2024 IROS article.

Aircraft Visual Inspection; A Benchmark of Machine Learning Models

Poster Session 1, Australasian Conference on Robotics & Automation (ACRA), 2024

Aircraft inspection benchmarks supervised and unsupervised models for fault detection. A custom aircraft defect dataset was developed. YOLO-NAS-L achieved an F2 score of 0.82, improving human accuracy by 14%. Unsupervised models reached ~80% accuracy on a public defect dataset.

Multi-Robot Exploration with Inferred Human Intent in Large-Scale Field Experiments: Lessons Learnt

Workshop on Real-World Challenges in Multi-Robot Cooperation, International Conference on Intelligent Robots and Systems (IROS), 2024

We provide lessons learned from developing a multi-robot system (MRS) for informative path planning in a large-scale field environment. Our heterogeneous MRS explores a hazardous area to ensure human safety. The primary lessons learned concern algorithm design for outdoor MRSs and the challenges posed by developmental robotic platforms. The conference invited our team to present due to winning the best paper award for this workshop.

Instructing Robots with Language via Bi-RNNs for Logic Translation

ACRA, 2023

We consider the problem of planning trajectories that satisfy natural language instruction, explore translating commands to logic formulae, and propose a Bi-RNN architecture for robot translation. The architecture achieves 1.6% better accuracy, 20% faster inference time, and 98% faster training time than leading models.

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Construction of the Minisatellite Survey: Modern Survey Design Considering Bias

American Geophysical Union, 2023

Organisations select quality attributes “ilities” based on desired system performance. Agency standards define ilities. Primes within the space segment use agency standards (E.g., NASA-STD-8739.9) and open-source systems (E.g., NASA cFS) to aid design. This poster presents a survey design and initial findings from a pilot collection of 100 respondents to identify how desired ilities are calculated. This poster provides methods to improve survey response rate considering bias.

An Ility Calculation for Satellite Software Validation

IEEE Aerospace, 2022

A quality attribute “ility” taxonomy tackling the complexities of satellite engineering. The research resulted in a collection of 345 ilities defined using agency and prime standards. Quality inputs for reliability, scalability, and adaptability are visualised.

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Dynamic Verification of Satellite Systems using Ilities

Journal of Space Safety Engineering, 2021

Bayesian estimation was applied to a NASA database of 219 smallsats (0.001–180 kg) failures from 2000 to 2016 to generate failure (reliability and survivability) categories. A communication system (47%) or attitude control (16%) failure is most likely to occur during a future NASA smallsat mission.

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Selection Factors Determining the Hybrid Approach

Americas Conference on Information Systems, 2020

The choice of methodology for information system development (ISD) is a significant question faced by information systems (IS) professionals. The study investigates factors that influence selection of a hybrid approach to ISD.

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Bray, E., Brown, M., Lee, K. M. B., Linstrom, F., Tan, A., Eyers, A., Sharma, S., Johnson, D., Fitch, R., Kong, F. H., & Best, G. (2024). Multi-Robot Exploration with Inferred Human Intent in Large-Scale Field Experiments: Lessons Learnt. Workshop on Real-World Challenges in Multi-Robot Cooperation, IROS. Available: https://www.researchgate.net/publication/384893740_Multi-Robot_Exploration_with_Inferred_Human_Intent_in_Large-Scale_Field_Experiments_Lessons_Learnt

Sharma, S., Lee, K. M. B., Brown, M., & Best, G. (2023). Instructing Robots with Natural Language via Bi-RNNs for Temporal Logic Translation. In Australasian Conference on Robotics and Automation. Available: https://www.researchgate.net/profile/Mason_Brown2/publication/376266308_Instructing_Robots_with_Natural_Language_via_Bi-RNNs_for_Temporal_Logic_Translation/links/65710e0fd21eb37cd4fa2b4e/Instructing-Robots-with-Natural-Language-via-Bi-RNNs-for-Temporal-Logic-Translation.pdf

Brown, M., Dey, S., & Tuxworth, G. (2023). Construction of the Minisatellite Survey: Modern Survey Design Considering Bias. In American Geophysical Union (AGU). iPoster. San Francisco, California, United States. Available: https://agu.confex.com/agu/fm23/meetingapp.cgi/Paper/1240609

Brown, M., Dey, S., Gervase, T., Burnus, P. and de Souza, P. (2022, February). An Ilities Tool for Satellite Software Validation [PowerPoint slides]. Institute for Integrated and Intelligent Systems, Griffith University.

Brown, M., Dey, S., Gervase, T., Burnus, P. and de Souza, P. (2022). Dynamic Verification of Satellite Systems using Ilities. Journal of Space Safety Engineering9 (1). Available: https://doi.org/10.1016/j.jsse.2022.02.009

Brown, M., Dey, S., Gervase, T., Co, J., Burnus, P. and de Souza, P. (2022, March). An Ility Calculation for Satellite Software Validation. In IEEE Aerospace Conference, the United States, pp. 1-20. IEEE. Available: https://ieeexplore.ieee.org/document/9843603

Brown, M., Dey, S., Gervase, T., Burnus, P. and de Souza, P. “Dynamic Verification of Satellite Systems using Ilities,” in the 11th International Association for the Advancement of Space Safety Conference, Netherlands, 2021, October, pp. 1-8. Available: http://iaassconference2021.space-safety.org/

Brown, M., Dey, S., & Tixworth, T. (2020). Selection Factors Determining the Hybrid Approach (Master's dissertation). Griffith University, Australia.

Brown, Mason C.; Dey, Sharmistha; and Tuxworth, Gervase, "SELECTION FACTORS DETERMINING THE HYBRID APPROACH: A PRELIMINARY STUDY" (2020). AMCIS 2020 Proceedings. 3.
Available: https://aisel.aisnet.org/amcis2020/systems_analysis_design/systems_analysis_design/3/