Asian Surveying & Mapping
Breaking News
HAL to build, market Isro’s SSLV in landmark deal
New Delhi, Jun 20: In a historic move for...
Taiwan developing space capabilities for all-weather imaging
TAIPEI (TVBS News) — Taiwan is advancing its space...
Honda hails successful test of reusable rocket as it looks to get into the space business
Tokyo — Japan's second-biggest carmaker, Honda, has successfully tested...
China’s space program provides larger platform for broader international cooperation
BEIJING -- Experts from China's manned space program said...
India To Launch $1.5 Billion Joint Earth Mission With NASA In July
National Aeronautics and Space Administration (NASA) and the Indian...
Axiom-4 mission delayed again: ISRO confirms Subhanshu Shukla’s ISS spaceflight won’t launch before 22 June 2025
The Axiom-4 mission to the International Space Station has...
Mengzhou spacecraft for China’s moon-landing mission passes landmark test flight
China has completed the inaugural test flight of its...
Space application for ITMA Asia + CITME 2026 opens
Shanghai – Space application for the 2026 edition of...
Yanmar, Chia Tai and XAG Empower Thai Agriculture through Innovation
Bang Nam Priao District, Chachoengsao Province, Thailand – On...
bitsensing Signs MOU with IKIO Technologies to Advance AI-Based Traffic Monitoring on India’s Expressways, Highways and Municipal Areas
Backed by proven success in South Korea and Europe,...
  • Jul 30, 2019
  • Comments Off on Researchers from University of Adelaide Win Global Pose Estimation Challenge
  • Feature
  • 955 Views

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.