Automated Tasking of RAS Teams for Active Modelling of CBRN Threats

Project Member(s): Bishop, D., Solntsev, A., Tran, T.

Funding or Partner Organisation: NSW Department of Industry (NSW Defence Innovation Network)
NSW Department of Industry (NSW Defence Innovation Network)

Start year: 2024

Summary: UTS will contribute to a UNSW-led project proposal to the Defence Innovation Network (DIN) The project will generate: 1) modelling methods (data structures and algorithms) for representing threat over an operational environment, given sampled hazard data; 2) an algorithm for near real-time updating of threat models based on new data obtained from Robotic and Autonomous Systems (RAS) assets; 3) an algorithm for tasking RAS assets to support optimal data gathering given model update requirements; 4) algorithms for autonomous execution of task plans/behaviours by RAS platforms; 5) measures of system performance and algorithms to evaluate these measures.

Publications:

Odebowale, AA, Abdulghani, A, Berhe, AM, Somaweera, D, Akter, S, Abdo, S, As’ham, K, Saadabad, RM, Tran, TT, Bishop, DP, Solntsev, AS, Miroshnichenko, AE & Hattori, HT, 'Emerging Low Detection Limit of Optically Activated Gas Sensors Based on 2D and Hybrid Nanostructures', Nanomaterials, vol. 14, no. 18, pp. 1521-1521.
View/Download from: Publisher's site

FOR Codes: Control engineering, mechatronics and robotics, Photonic and electro-optical devices, sensors and systems (excl. communications), Software engineering, Emerging defence technologies

Acknowledgement of Country

UTS acknowledges the Gadigal people of the Eora Nation, the Boorooberongal people of the Dharug Nation, the Bidiagal people and the Gamaygal people, upon whose ancestral lands our university stands. We would also like to pay respect to the Elders both past and present, acknowledging them as the traditional custodians of knowledge for these lands.