极性-时间交互与多层可靠性的事件相机航天器位姿估计框架
Polarity--Time Interaction and Multi-Level Reliability for Event-Based Spacecraft Pose Estimation
AI 导读
一种面向事件相机航天器位姿估计的可靠性感知框架，整合极性-时间定位、几何恢复、事件-CAD 精化与轨迹优化，采用正负事件与近期事件时间的三分支表示及十维描述子设定观测尺度。
正文 · 原文
Abstract:Sparse event responses produce uneven keypoint errors whose effects on spacecraft pose depend on correspondence geometry and the reliability of successive observations. We present a reliability-aware framework connecting polarity--time localization, geometric recovery, event--CAD refinement, and trajectory optimization. A three-branch representation combines positive events, negative events, and recent-event timing through cross-branch attention and gating, followed by spatiotemporal aggregation. An ordered semantic-point head estimates relative correspondence precision for geometrically constrained pose recovery. Event-edge and CAD-projection agreement then guide local pose refinement under keypoint-geometry safeguards. At the sequence level, a ten-dimensional descriptor combines heatmap shape, reprojection consistency, and geometric conditioning to set time-aligned observation scales. On the official SPADES challenge test set, the complete system achieves a combined pose score of 0.0474, approximately 5.4\% below PASAN+IRIS. Validation ablations reduce the score from 0.0772 for base localization with uniform PnP to 0.0514 for the complete cascade; on identical single-frame observations, quality weighting reduces the score from 0.0549 with constant-weight optimization to 0.0514.
| Subjects: | Artificial Intelligence (cs.AI); Robotics (cs.RO) |
| Cite as: | arXiv:2610.36625 [cs.AI] |
| (or arXiv:2610.36625v1 [cs.AI] for this version) | |
| https://doi.org/10.48550/arXiv.2610.36625 arXiv-issued DOI via DataCite (pending registration) |
Submission history
From: Yonglong Zhang [view email]
[v1]
Tue, 27 Oct 2026 04:29:19 UTC (464 KB)
来源：arXiv cs.AI · arxiv.org