On-Orbit Space AI: Federated, Multi-Agent, and Collaborative Algorithms for Satellite Constellations

• URL: http://arxiv.org/abs/2604.16518v1
• Date: Wed, 15 Apr 2026 16:15:47 GMT
• Title: On-Orbit Space AI: Federated, Multi-Agent, and Collaborative Algorithms for Satellite Constellations
• Abstract summary: Satellite constellations are transforming space systems from isolated spacecraft into networked, software-defined platforms capable of on-orbit perception, decision making, and adaptation.<n>This survey consolidates the emerging field of on-orbit space AI through three complementary paradigms: (i) federated learning for cross-satellite training, personalization, and secure aggregation; (ii) multi-agent algorithms for cooperative planning, resource allocation, scheduling, formation control, and collision avoidance; and (iii) collaborative sensing and distributed inference for multi-satellite fusion, tracking, split/early-exit inference, and cross-layer co-design
• Score: 17.969021804498844
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Satellite constellations are transforming space systems from isolated spacecraft into networked, software-defined platforms capable of on-orbit perception, decision making, and adaptation. Yet much of the existing AI studies remains centered on single-satellite inference, while constellation-scale autonomy introduces fundamentally new algorithmic requirements: learning and coordination under dynamic inter-satellite connectivity, strict SWaP-C limits, radiation-induced faults, non-IID data, concept drift, and safety-critical operational constraints. This survey consolidates the emerging field of on-orbit space AI through three complementary paradigms: (i) {federated learning} for cross-satellite training, personalization, and secure aggregation; (ii) {multi-agent algorithms} for cooperative planning, resource allocation, scheduling, formation control, and collision avoidance; and (iii) {collaborative sensing and distributed inference} for multi-satellite fusion, tracking, split/early-exit inference, and cross-layer co-design with constellation networking. We provide a system-level view and a taxonomy that unifies collaboration architectures, temporal mechanisms, and trust models. To support community development and keep this review actionable over time, we continuously curate relevant papers and resources at https://github.com/ziyangwang007/AI4Space.

Related papers

• FractalNet-Based Heterogeneous Federated Learning for Orbital Edge Intelligence in Satellite Mega-Constellations: A Wildfire Case Study [0.3093890460224435]
  mega-constellations are emerging as large-scale sensing, communication, and computation fabrics.<n>We propose a heterogeneous federated learning method based on the FractalNet architecture for orbital edge intelligence.<n> Experiments on simulated mega-constellations validate the approach across convergence, communication efficiency, energy adaptation, scheduled-pooling savings, robustness, and latency.
  arXiv  Detail & Related papers  (2026-09-01T08:07:39Z)
• Reinforcement Learning-Guided Evolutionary Policy Optimization for Preference-Adjustable Heterogeneous Agile Earth Observation Satellite Scheduling [50.176885352114674]
  Heterogeneous agile Earth observation satellite (AEOS) scheduling requires task selection, satellite assignment, and observation sequencing.<n>This paper proposes an evolutionary policy optimization framework for heterogeneous AEOS scheduling with preference-adjustable weighted objectives.
  arXiv  Detail & Related papers  (2026-08-25T12:16:28Z)
• IMAGINE: Intelligent Multi-Agent Godot-based Indoor Networked Exploration [0.0]
  This paper implements Multi-Agent Reinforcement Learning (MARL) to address challenges in a 2D indoor environment.<n>Policy training aims to achieve emergent collaborative behaviours and decision-making under uncertainty.
  arXiv  Detail & Related papers  (2026-02-02T22:08:41Z)
• Large-Scale Continual Scheduling and Execution for Dynamic Distributed Satellite Constellation Observation Allocation [1.3467991712339638]
  Deploying autonomy to satellites requires efficient computation and communication.<n>We present the Dynamic Multi-Satellite Constellation Observation Scheduling Problem (DCOSP)<n>We also present the Dynamic Incremental Neighborhood Search algorithm (D-NSS)
  arXiv  Detail & Related papers  (2026-01-08T00:10:45Z)
• Towards 6G Native-AI Edge Networks: A Semantic-Aware and Agentic Intelligence Paradigm [85.7583231789615]
  6G positions intelligence as a native network capability, transforming the design of radio access networks (RANs)<n>Within this vision, Semantic-native communication and agentic intelligence are expected to play central roles.<n>Agentic intelligence endows distributed RAN entities with goal-driven autonomy, reasoning, planning, and multi-agent collaboration.
  arXiv  Detail & Related papers  (2025-12-04T03:09:33Z)
• Joint AoI and Handover Optimization in Space-Air-Ground Integrated Network [48.485907216785904]
  Low Earth orbit (LEO) satellite constellations offer promising solutions with global coverage and reduced latency.<n>Yet struggle with intermittent coverage and intermittent communication windows due to orbital dynamics.<n>Our three-layer design employs hybrid free-space optical (FSO) links for high-capacity satellite-to-ground communication and reliable radio frequency (RF) links for HAP-to-ground transmission.
  arXiv  Detail & Related papers  (2025-09-16T06:16:56Z)
• A Survey on Cloud-Edge-Terminal Collaborative Intelligence in AIoT Networks [49.90474228895655]
  Cloud-edge-terminal collaborative intelligence (CETCI) is a fundamental paradigm within the artificial intelligence of things (AIoT) community.<n>CETCI has made significant progress with emerging AIoT applications, moving beyond isolated layer optimization to deployable collaborative intelligence systems.<n>This survey describes foundational architectures, enabling technologies, and scenarios of CETCI paradigms, offering a tutorial-style review for CISAIOT beginners.
  arXiv  Detail & Related papers  (2025-08-26T08:38:01Z)
• Space-O-RAN: Enabling Intelligent, Open, and Interoperable Non Terrestrial Networks in 6G [16.472121677010268]
  This paper introduces Space-O-RAN, a distributed control architecture that extends Open RAN principles into satellite constellations through hierarchical, closed-loop control.<n>Lightweight glspldapp operate onboard satellites, enabling real-time functions like scheduling and beam steering without relying on persistent ground access.<n>A key enabler is the dynamic mapping of the O-RAN interfaces to satellite links, supporting adaptive signaling under varying conditions.
  arXiv  Detail & Related papers  (2025-02-21T21:03:37Z)
• Distributed satellite information networks: Architecture, enabling technologies, and trends [56.747473208256174]
  The distributed satellite information networks (DSIN) have emerged as an innovative architecture, bridging information gaps across diverse satellite systems.<n>This survey first provides a profound discussion about innovative network architectures of DSIN.<n>The DSIN faces challenges from network heterogeneity, unpredictable channel dynamics, sparse resources, and decentralized collaboration frameworks.
  arXiv  Detail & Related papers  (2024-12-17T06:44:05Z)
• A Distance Similarity-based Genetic Optimization Algorithm for Satellite Ground Network Planning Considering Feeding Mode [53.71516191515285]
  The low transmission efficiency of the satellite data relay back mission has become a problem that is currently constraining the construction of the system. We propose a distance similarity-based genetic optimization algorithm (DSGA), which considers the state characteristics between the tasks and introduces a weighted Euclidean distance method to determine the similarity between the tasks.
  arXiv  Detail & Related papers  (2024-08-29T06:57:45Z)
• Towards Autonomous Satellite Communications: An AI-based Framework to Address System-level Challenges [0.0]
  The next generation of satellite constellations is designed to better address the future needs of our connected society. There is still not a clear path to achieve fully-autonomous satellite systems. In this paper we try to bridge this gap by characterizing the system-level needs that must be met to increase satellite autonomy.
  arXiv  Detail & Related papers  (2021-12-11T19:36:58Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.