Code & Software

This is our code and software GitHub organisation.

With the intent of enabling a higher level of research and development collaboration among robotics research organisations and industry partners in Australia and internationally, below you can find a growing list of our research projects’ codes and software available for download.

• InCloud: Incremental Learning for Point Cloud Place Recognition: To access the code, visit the InCloud code page
• What’s in the Black Box? The False Negative Mechanisms Inside Object Detectors: To access the code, visit the Fn_mechanisms code page
• LoGG3D-Net: Locally Guided Global Descriptor Learning for 3D Place Recognition: To access the code, visit the LoGG3D-Net code page
• Canopy density estimation in perennial horticulture crops using 3D spinning lidar SLAM (AgScan3D) To access the code, visit the AgScan3D code page
• Locus: LiDAR-based Place Recognition using Spatiotemporal Higher-Order Pooling: To access the code, visit the Locus code page
• Temporally Coherent Embedding for Self-Supervised Video Representation Learning (TCE): To access the code, visit the TCE code page and to learn about this project, click here.
• Scalable learning for bridging the species gap in image-based plant phenotyping: To access the code, visit the code page and to learn about this project, click here.
• OpenSHC: A Versatile Multilegged Robot Controller: To access the code, visit the code page and to learn about this project, click here.

For more information, contact us.