Rapidscan - Enhanced Time Domain Signal Processing Methods for LiDar as Payload on Autonomous Systems (Part A)

Project Member(s): Oberst, S., Halkon, B., Fitch, R.

Funding or Partner Organisation: Department of Industry, Innovation and Science (Innovation Connections)
Department of Industry, Innovation and Science (Innovation Connections)
Robotic Systems Pty Ltd
Robotic Systems Pty Ltd

Start year: 2020

Summary: Development of enhanced signal processing for a LiDar device (Rapidscan) as payload on autonomous systems (UAVs, walking hexapods).

Publications:

Darwish, A, Halkon, B & Oberst, S 2022, 'Non-Contact Vibro-Acoustic Object Recognition Using Laser Doppler Vibrometry and Convolutional Neural Networks', Sensors, vol. 22, no. 23, pp. 9360-9360.
View/Download from: Publisher's site

Darwish, A, Oberst, S & Halkon, B University of Technology Sydney 2022, Hexapod payload report, no. v1, Centre for Audio, Acoustics and Vibration, Faculty of Engineering and IT, University of Technology Sydney.

FOR Codes: Acoustics and noise control (excl. architectural acoustics), 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.