Evaluation of Resource-Efficient Crater Detectors on Embedded Systems
实时分析火星坑对于任务关键操作（包括安全着陆和地质勘探）至关重要。这项工作利用了空间船上最先进的突破来进行边缘坑检测。我们用火星坑数据集 rigorously 基准了几个 YOLO 网络，重点分析它们在低功耗设备上的嵌入系统中的性能，为减小成本的商业现货卫星优化这个过程。我们在 Google Coral Edge TPU、AMD Versal SoC VCK190、Nvidia Jetson Nano 和 Jetson AGX Orin 等各种平台上实施这种优化。我们的研究结果确定最佳的网络与设备对，提高了在资源受限硬件上进行坑检测的可行性，并为高效和弹性的外太空成像树立了新的先例。代码在此处：https:// 这个链接。
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: this https URL.
https://arxiv.org/abs/2405.16953
https://arxiv.org/pdf/2405.16953.pdf