Asian Surveying & Mapping
Breaking News
This dashboard uses GIS to track COVID-19 cases in real-time
Coronavirus cases have seen a significant jump in India...
Satellite animation shows air pollution in China and Italy clearing amid coronavirus lockdowns
In countries and regions that have been under strict...
ISRO has planned a total of 36 missions for 2020-21
2020 and 2021, these two years are going to...
UAE’s student-built climate observation satellite to launch this summer
The UAE will be launching a student-built nanosatellite that...
Space to grow global defence
Global defence company Nova Group is maintaining its projections...
Exolaunch to deliver UAE Space Agency’s small satellite into orbit on Soyuz-2
Berlin-based Exolaunch has told SpaceDaily that the launch of...
Toyota taps startup Momenta to build HD road maps in China
HONG KONG -- Toyota Motor has teamed up with...
Economic lockdown ‘reduces global pollution levels’ – European Space Agency
The lockdown aimed at combating the spread of COVID-19...
A ‘travel log’ of the times in South Korea: Mapping the movements of coronavirus carriers
SEOUL — The novel coronavirus outbreak has produced at...
China’s polar-observation satellite completes Antarctic mission
China's first polar-observation satellite has completed its Antarctic observation...

The team of researchers from the University of Adelaide’s Australian Institute for Machine Learning (AILM) defeated 47 other universities and space technology companies at the international space competition hosted by the European Space Agency.

The South Australian team—including Associate Professor Tat-Jun Chin, Dr. Bo Chen and Dr. Alvaro Parra Bustos—won the challenge to determine the most accurate orientation of an object in space by using machine learning and 3D vision algorithms.

Teams were given individual high-fidelity images of the Tango spacecraft from the 2016 PRISMA mission and were required to determine the orientation of the craft in relation to the observer from close rendezvous.

The goal of the challenge was to estimate the pose—the relative position and attitude—of a known spacecraft in order to help future space missions.

Knowing the exact pose enables the development of debris-removal technologies, refurbishment of expensive space assets, and the development of space depots to facilitate travel toward distant destinations.