AQ-PCDSys: An Adaptive Quantized Planetary Crater Detection System for Autonomous Space Exploration
This work addresses a critical problem for autonomous space exploration missions by enabling reliable, onboard environmental perception, though it appears incremental as it builds on existing quantization and fusion techniques.
The paper tackled the challenge of deploying deep learning models for real-time crater detection on resource-constrained planetary exploration platforms by introducing AQ-PCDSys, which integrates quantized neural networks and adaptive multi-sensor fusion to optimize model size and inference latency while preserving high accuracy.
Autonomous planetary exploration missions are critically dependent on real-time, accurate environmental perception for navigation and hazard avoidance. However, deploying deep learning models on the resource-constrained computational hardware of planetary exploration platforms remains a significant challenge. This paper introduces the Adaptive Quantized Planetary Crater Detection System (AQ-PCDSys), a novel framework specifically engineered for real-time, onboard deployment in the computationally constrained environments of space exploration missions. AQ-PCDSys synergistically integrates a Quantized Neural Network (QNN) architecture, trained using Quantization-Aware Training (QAT), with an Adaptive Multi-Sensor Fusion (AMF) module. The QNN architecture significantly optimizes model size and inference latency suitable for real-time onboard deployment in space exploration missions, while preserving high accuracy. The AMF module intelligently fuses data from Optical Imagery (OI) and Digital Elevation Models (DEMs) at the feature level, utilizing an Adaptive Weighting Mechanism (AWM) to dynamically prioritize the most relevant and reliable sensor modality based on planetary ambient conditions. This approach enhances detection robustness across diverse planetary landscapes. Paired with Multi-Scale Detection Heads specifically designed for robust and efficient detection of craters across a wide range of sizes, AQ-PCDSys provides a computationally efficient, reliable and accurate solution for planetary crater detection, a critical capability for enabling the next generation of autonomous planetary landing, navigation, and scientific exploration.