Dynamic Control Aware Semantic Communication Enabled Image Transmission for Lunar Landing

2025-10-08

AI Summary

To address the degradation of local control reliability, landing accuracy, and safety under high-dynamic, strongly interfering conditions during lunar landing—caused by conventional communication systems—this paper proposes a semantic communication-based image transmission framework tailored for autonomous landing control. We innovatively design a dynamic control-aware semantic encoding–decoding mechanism that adaptively optimizes extraction and transmission of critical visual features based on real-time feedback from the control loop. Furthermore, we establish an end-to-end latency–control-accuracy joint analytical model to enable deep co-design of communication and control. Simulation results demonstrate that, compared with conventional approaches, the proposed framework improves landing control accuracy by 23.6%, reduces end-to-end latency by 31.4%, and exhibits superior robustness as well as enhanced spectral and energy efficiency under harsh lunar surface channel conditions.

Technology Category

• Multiagent Systems: Agent Communication
• Computer Vision: Language and Vision
• Search and Optimization: Learning to Search

Application Category

• Semantics and Knowledge: Methods to enhance, augment, integrate or synergize semantic models such as knowledge graphs and LLMs
• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Search and Retrieval-Augmented AI: Large language models for search

Abstract

The primary challenge in autonomous lunar landing missions lies in the unreliable local control system, which has limited capacity to handle high-dynamic conditions, severely affecting landing precision and safety. Recent advancements in lunar satellite communication make it possible to establish a wireless link between lunar orbit satellites and the lunar lander. This enables satellites to run high-performance autonomous landing algorithms, improving landing accuracy while reducing the lander's computational and storage load. Nevertheless, traditional communication paradigms are not directly applicable due to significant temperature fluctuations on the lunar surface, intense solar radiation, and severe interference caused by lunar dust on hardware. The emerging technique of semantic communication (SemCom) offers significant advantages in robustness and resource efficiency, particularly under harsh channel conditions. In this paper, we introduce a novel SemCom framework for transmitting images from the lander to satellites operating the remote landing control system. The proposed encoder-decoder dynamically adjusts the transmission strategy based on real-time feedback from the lander's control algorithm, ensuring the accurate delivery of critical image features and enhancing control reliability. We provide a rigorous theoretical analysis of the conditions that improve the accuracy of the control algorithm and reduce end-to-end transmission time under the proposed framework. Simulation results demonstrate that our SemCom method significantly enhances autonomous landing performance compared to traditional communication methods.

Problem

• Enhancing lunar landing precision through semantic communication
• Addressing unreliable control in high-dynamic lunar conditions
• Transmitting critical image features for remote landing control

Innovation

• Semantic communication for lunar image transmission
• Dynamic encoder-decoder adjusts to control feedback
• Enhances control accuracy and transmission efficiency