106 citations · 199 across the 7 of their papers we have counts for
9 papers
Autonomous 3D Visual-Thermal Inspection for Utility-Scale Solar Farms
Lachlan Tychsen-Smith, Mark Cox, Brett Wood +6
Utility-scale photovoltaic (PV) inspection is dominated by aerial surveys, which are effective for identifying module-level hot cells but provide limited visibility of critical com…
Heterogeneous robot teams with unified perception and autonomy: How Team CSIRO Data61 tied for the top score at the DARPA Subterranean Challenge
Navinda Kottege, Jason Williams, Brendan Tidd +27
The DARPA Subterranean Challenge was designed for competitors to develop and deploy teams of autonomous robots to explore difficult unknown underground environments. Categorised in…
A Real-time Edge-AI System for Reef Surveys
Yang Li, Jiajun Liu, Brano Kusy +12
Crown-of-Thorn Starfish (COTS) outbreaks are a major cause of coral loss on the Great Barrier Reef (GBR) and substantial surveillance and control programs are ongoing to manage COT…
Monitoring of Pigmented Skin Lesions Using 3D Whole Body Imaging
David Ahmedt-Aristizabal, Chuong Nguyen, Lachlan Tychsen-Smith +5
Advanced artificial intelligence and machine learning have great potential to redefine how skin lesions are detected, mapped, tracked and documented. Here, We propose a 3D whole-bo…
Continuous Human Action Recognition for Human-Machine Interaction: A Review
Harshala Gammulle, David Ahmedt-Aristizabal, Simon Denman +3
With advances in data-driven machine learning research, a wide variety of prediction models have been proposed to capture spatio-temporal features for the analysis of video streams…
The CSIRO Crown-of-Thorn Starfish Detection Dataset
Jiajun Liu, Brano Kusy, Ross Marchant +17
Crown-of-Thorn Starfish (COTS) outbreaks are a major cause of coral loss on the Great Barrier Reef (GBR) and substantial surveillance and control programs are underway in an attemp…
Heterogeneous Ground and Air Platforms, Homogeneous Sensing: Team CSIRO Data61's Approach to the DARPA Subterranean Challenge
Nicolas Hudson, Fletcher Talbot, Mark Cox +31
Heterogeneous teams of robots, leveraging a balance between autonomy and human interaction, bring powerful capabilities to the problem of exploring dangerous, unstructured subterra…
Improving Object Localization with Fitness NMS and Bounded IoU Loss
Lachlan Tychsen-Smith, Lars Petersson
We demonstrate that many detection methods are designed to identify only a sufficently accurate bounding box, rather than the best available one. To address this issue we propose a…
DeNet: Scalable Real-time Object Detection with Directed Sparse Sampling
Lachlan Tychsen-Smith, Lars Petersson
We define the object detection from imagery problem as estimating a very large but extremely sparse bounding box dependent probability distribution. Subsequently we identify a spar…