Asian Surveying & Mapping
Breaking News
ISRO Maps Over 2,000 Glaciers, 3,219 Glacial Lakes in Ladakh for Disaster Management
SRINAGAR: The Indian Space Research Organisation (ISRO) and other...
China Closes the Satellite Gap in Space Race With the U.S.
China aims to match the U.S. as the world’s...
IIT-Tirupati hosts fifth BRICS working group meeting on geospatial technologies
The Indian Institute of Technology-Tirupati (IIT-Tirupati), in collaboration with...
South Korea launches 4th Earth observation satellite from US
South Korea on Tuesday launched its fourth Earth observation...
Korea AeroSpace Administration Unveils K-Space Vision
Agency Will Benchmark European Aerospace Clusters and Explore Joint...
Japan space agency conducts Epsilon rocket engine test after failures
TOKYO - The Japan Aerospace Exploration Agency on Thursday...
UAE to boldly go with programme to boost nation’s expertise in space sector
A programme has been announced to enhance Emirati expertise...
China is building a ‘Mach 26 asteroid hammer’ to strike space rocks before they hit Earth
The Earth revolves in a cosmic system which is...
Nigeria and Benin Strengthen Border Surveillance with Geospatial Technology
The partnership was highlighted during a strategic meeting at...
IIT-Tirupati hosts fifth BRICS working group meeting on geospatial technologies
The Indian Institute of Technology-Tirupati (IIT-Tirupati), in collaboration with...
  • Jul 30, 2019
  • Comments Off on Researchers from University of Adelaide Win Global Pose Estimation Challenge
  • Feature
  • 1261 Views

July 30th, 2019
Researchers from University of Adelaide Win Global Pose Estimation Challenge

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.