LATIDIA · Robótica

Estimación de pose basada en la visión correcta por construcción utilizando modelos generativos geométricos

arXiv: 2601.17556v2Tipo de anuncio: reemplazar Resumen: Consideramos el problema de la estimación de pose basada en la visión para sistemas autónomos. Si bien las redes neuronales profundas se han utilizado con éxito para tareas basadas en la visión,

La noticia

arXiv:2601.17556v2 Announce Type: replace Abstract: We consider the problem of vision-based pose estimation for autonomous systems. While deep neural networks have been successfully used for vision-based tasks, they inherently lack provable guarantees on the correctness of their output, which is crucial for safety-critical applications. We present a framework for designing certifiable neural networks (NNs) for perception-based pose estimation that integrates physics-driven modeling with learning-based estimation. The proposed framework begins by leveraging the known geometry of planar objects commonly found in the environment, such as traffic signs and runway markings, referred to as target objects. At its core, it introduces a geometric generative model (GGM), a neural-network-like model whose parameters are