Very exciting news from Antikythera in Greece, where we conducted mapping with the AUV Sirius in 2014 and 2015. Archaeologists have announced the discovery of 2000 year old bones on the site. The map generated by our AUV is featured in this article and shows the location of some of the artefacts recovered from the site. Kudos to the whole team involved in supporting this work, and in particular Oscar Pizarro and Christian Lees who helped make it all happen. [September 19th, 2016]
Congratulations again to William Reid for his invited talk at the MATLAB Conference 2016. Watch his presentation on Rapid Algorithm Development for Planning and Control of an Actively Articulated Wheel-on-Leg Robot here. [July 25, 2016]
ACFR took part in the Robotics for Good competition held in Dubai this month. We came 4th, which is quite an achievement. The team had a great time and learnt a lot from the experience. Special thanks and congratulations to Will, Steven, Javier, Akash, Esa, Thomas, Vinny, Dewey and Seva, who all put in some late nights to get the submission in, the logistics, and the actual support on the day of the competition. Follow the link to find out more. [February 10, 2016]
Congratulations to Stefan Williams and Oscar Pizarro on their ARC Linkage grant success. Their project aims to develop novel acoustic communication schemes that will allow communication between a human operator and an underwater robot, exploiting developments in machine learning, network and communication theory. [July 14, 2015]
The Mars Lab - A short promotional video on the work ACFR have been doing on STEM and the Mars Rover for the past 3 years [June 11, 2015].
Congratulations to Mitchell Bryson for being awarded the Mid-Career Researcher Award for his project 'Visual, hyperspectral and thermal imaging fusion using low-cost sensors for agri-food applications.' This project will develop innovative low-cost solutions to acquiring and processing hyper spectral and thermal infrared imagery used for assessing agricultural crop biophysical parameters. The high-costs and/or lack of spatial/temporal resolution in existing techniques limit the use of this information in smallholder farming or farming operations in developing nations that face the largest challenges in meeting food production targets in the coming decades. Cutting-edge techniques in image processing, sensor fusion and machine learning will be used produce high-resolution maps using low-cost sensors from which agriculturally-relevant biophysical parameters such as biomass, productivity, water and nutrient stress of agricultural crops can be inferred [June 5, 2015].