While geopolitical tensions pull the world apart, human nature and business opportunities have driven globalisation. In the realm of space, what began as a race between the world’s superpowers entered a new age with human spaceflight.
Since the launch of the International Space Station, collaboration in space has been a continued success.
Renewed Collaboration
The Moon Village concept and the Artemis space programme all include major space-faring nations and their actors as partners. There can be no doubt that space exploration brings and keeps people from various nations together. The same spirit of collaboration will be needed for meaningful space sustainability, safety and security.
The economic, social, environmental, and political importance of space leaves us with no choice but to tackle the various issues of space spatial awareness, debris threats, and space traffic management at a multi-national and global level. New Space means many different things, but it also means private investments, placing space no longer just as the remit of public institutions and governments.
Where governments do not agree, businesses will build bridges that no conflict can tear down. There’s a need to put all our efforts into making space sustainability and safety a reality.
In the world of operations and space situational awareness, it is essential to understand the various resident space objects (RSOs) in orbit and their behaviour.
Common Framework
Factors influencing behaviour in space can be better understood through a well-established taxonomy that can facilitate research and analysis by providing a common language and framework. These factors, in turn, help design more efficient and effective strategies for space traffic management and are a foundational aspect of a shared set of guidelines or rules of the road. AI and Machine Learning are key to enabling in-space automation and autonomy.
This implies E4-level autonomy (i.e., goal-oriented autonomy), as defined by the European Space Agency. This level of autonomy means that a system is capable of autonomously deliberating on the mission’s goals and tasks and re-planning activities it needs to perform. Goal reasoning studies how autonomous agents can dynamically reason about and adjust their goals.
Two models for goal reasoning are Goal- Driven Autonomy (GDA), which allows an autonomous agent to not only manage existing goals but also introduce new goals and pre-empt active goals and Goal Lifecycle (GL), whereby goals transition through stages of increasingly detailed modes by activating a series of refinement strategies.
We hope that where governments do not agree, businesses will build bridges that no conflict can tear down. There’s a need to put all our efforts into making space sustainability and safety a reality.
Disclaimer: Views Expressed are Author's Own. Geospatial World May or May Not Endorse it
