MR Roboto - Stage 1 - Scoping study and prototype digital twin

Project Member(s): Paul, G., Kodagoda, S., Munasinghe, N., Vu, T., Valls Miro, J.

Funding or Partner Organisation: NEXTORE PTY LTD
NEXTORE PTY LTD

Start year: 2022

Summary: In this project UTS:RI aims to deliver a sensing and control solution to NextOre for a geometry sensing system to inform the robotic control and positioning of a large-scale Magnetic Resonance (MR) sensor. The aims and deliverables are proposed in multiple stages as proposed by partner, and open to further discussion. The timeline of Stages 2, and the existence of Stage 3, depend on the outcome of the NSSN Challenge. Scoping study, prototype digital twin and NSSN Grand Challenge application (Nov 2021-Feb 2022). This Stage 1 is a scoping study to provide geometry-sensor selection advice, produce a prototype digital twin and complete the NSSN Grand Challenge proposal. This stage of the project has the following aims: - Determine and recommend appropriate laser sensors given the dusty mining environment, requirements about point cloud density, sensor mounting locations. - Advise on the optimal mounting location for laser sensors based on a digital-twin simulation. - Collect laser data from a single sensor and create a convex hull for load volume estimation. - Create an operationally equivalent model of the MR crane robot – “MR-Roboto” – simulated in Matlab. - Estimate MR sensing potential from a given location using a simple hemispheric model. - Collaboratively write an NSSN Grand Challenge [10] application proposal with NextOre. - Supply digital twin models and report write-up.

Publications:

Vu, TL, Nguyen, DDK, Sutjipto, S, Le, DT & Paul, G 2022, 'Investigation of User Performance in Virtual Reality-based Annotation-assisted Remote Robot Control', ACM, pp. 1-2.
View/Download from: Publisher's site

FOR Codes: Control engineering, mechatronics and robotics, Artificial intelligence, Primary mining and extraction of minerals, Industrial machinery and equipment

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.