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.
@article{arxiv.2405.16953,
title = {Evaluation of Resource-Efficient Crater Detectors on Embedded Systems},
author = {Simon Vellas and Bill Psomas and Kalliopi Karadima and Dimitrios Danopoulos and Alexandros Paterakis and George Lentaris and Dimitrios Soudris and Konstantinos Karantzalos},
journal= {arXiv preprint arXiv:2405.16953},
year = {2024}
}
Comments
Accepted at 2024 IEEE International Geoscience and Remote Sensing Symposium