Deep Learning for Real Time Satellite Pose Estimation on Low Power Edge TPU. (arXiv:2204.03296v2 [cs.CV] UPDATED)

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 learning edge learning low power power satellite time tpu