Real-time analysis of Martian craters is crucial for mission-critical operations, including safe landings and geological exploration. This work leverages the latest breakthroughs for on-the-edge crater detection aboard spacecraft. We rigorously benchmark several YOLO networks using a Mars craters dataset, analyzing their performance on embedded systems with a focus on optimization for low-power devices. We optimize this process for a new wave of cost-effective, commercial-off-the-shelf-based smaller satellites. Implementations on diverse platforms, including Google Coral Edge TPU, AMD Versal SoC VCK190, Nvidia Jetson Nano and Jetson AGX Orin, undergo a detailed trade-off analysis. Our findings identify optimal network-device pairings, enhancing the feasibility of crater detection on resource-constrained hardware and setting a new precedent for efficient and resilient extraterrestrial imaging. Code at: https://github.com/billpsomas/mars_crater_detection.

火星陨石坑的实时分析对任务关键操作至关重要，包括安全降落和地质探测。本研究利用最新突破，实现了在航天器上对陨石坑的边缘检测。我们在火星陨石坑数据集上对几个YOLO网络进行了严格的基准测试，分析了它们在嵌入式系统上的性能，重点优化低功耗设备。我们为新一代成本效益高、基于商用现成产品的较小卫星进行了优化。在包括Google Coral Edge TPU、AMD Versal SoC VCK190、Nvidia Jetson Nano和Jetson AGX Orin在内的多种平台上进行了详细的权衡分析。我们的研究结果确定了最佳的网络设备配对，提高了在资源受限硬件上进行陨石坑检测的可行性，为高效和弹性的星际图像处理设定了新的先例。代码：该网址链接。

嵌入式系统上资源高效的撞击坑检测器评估