What are the latest developments in spacecraft autonomy and artificial intelligence?

1 Self-healing software

One of the challenges of spacecraft autonomy is to ensure the reliability and robustness of the software systems that control the spacecraft functions. Self-healing software is a type of software that can detect, diagnose, and repair faults without human intervention. For example, NASA's Remote Agent Experiment (RAX) demonstrated the first self-healing software on board the Deep Space 1 spacecraft in 1999. Since then, several projects have explored different approaches to self-healing software, such as model-based reasoning, genetic algorithms, and neural networks.

2 Deep reinforcement learning

Another challenge of spacecraft autonomy is to enable the spacecraft to learn from its own experience and adapt to changing environments. Deep reinforcement learning (DRL) is a branch of AI that combines deep neural networks with reinforcement learning, a technique that rewards or penalizes the agent based on its actions and outcomes. For example, ESA's Advanced Concepts Team (ACT) developed a DRL algorithm that can autonomously control the attitude and orbit of a CubeSat. The algorithm can learn from scratch and optimize its performance over time.

3 Swarm intelligence

A third challenge of spacecraft autonomy is to coordinate multiple spacecraft that operate as a collective system. Swarm intelligence is a concept that mimics the behavior of natural swarms, such as ants, bees, or birds, to achieve complex tasks that are beyond the capabilities of individual agents. For example, NASA's Starling project aims to create a swarm of nanosatellites that can perform distributed sensing, communication, and computation. The swarm can self-organize, self-adapt, and self-heal based on local interactions and global objectives.

4 Cognitive architectures

A fourth challenge of spacecraft autonomy is to endow the spacecraft with higher-level cognitive functions, such as reasoning, planning, decision making, and problem solving. Cognitive architectures are frameworks that integrate various cognitive components and processes into a coherent system. For example, NASA's Autonomous Sciencecraft Experiment (ASE) used a cognitive architecture called CLARAty to enable the EO-1 spacecraft to autonomously select and execute science observations. The cognitive architecture can also generate and execute contingency plans, interpret data, and communicate with other spacecraft.

5 Future directions

The field of spacecraft autonomy and AI is rapidly advancing, with new directions such as more advanced self-healing software, the application of DRL to complex scenarios, and the exploration of swarm intelligence for large-scale missions. Additionally, cognitive architectures are incorporating more human-like cognitive functions, like creativity and curiosity. These technologies are not only improving current and future missions, but also opening up new possibilities for space exploration and discovery. It is exciting to consider how they will shape the future of the space industry.