Web: http://arxiv.org/abs/2204.03296

June 24, 2022, 1:12 a.m. | Alessandro Lotti, Dario Modenini, Paolo Tortora, Massimiliano Saponara, Maria A. Perino

cs.CV updates on arXiv.org arxiv.org

Pose estimation of an uncooperative space resident object is a key asset
towards autonomy in close proximity operations. In this context monocular
cameras are a valuable solution because of their low system requirements.
However, the associated image processing algorithms are either too
computationally expensive for real time on-board implementation, or not enough
accurate. In this paper we propose a pose estimation software exploiting neural
network architectures which can be scaled to different accuracy-latency
trade-offs. We designed our pipeline to be …

arxiv cv deep deep learning edge learning low power on power satellite time tpu

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