arXiv:2609.21597v1 Announce Type: new Abstract: Monocular 6-DoF pose estimation of non-cooperative targets is important for on-orbit servicing and debris removal. A single-image estimator can confuse...
arXiv:2610.07231v1 Announce Type: cross Abstract: This work presents a novel learning-based pipeline for pose estimation of unknown spacecraft using only monocular images from a single servicer. The...
arXiv:2609.13777v1 Announce Type: cross Abstract: Learned components are increasingly integrated into geometric visual--inertial estimators to provide motion, depth, bias, uncertainty, or confidence...
The paper introduces CalfVO, a monocular visual odometry system that operates without camera intrinsics, test‑time optimization, bundle adjustment, or loop closure. Using a transformer, it predicts relative poses with separate rotation and translation confidences over overlapping image windows, then aggregates these predictions via a confidence‑weighted module to produce a single trajectory. CalfVO achieves the highest accuracy among calibration‑free methods across five benchmarks and runs at 53 FPS, outperforming all baselines.
arXiv:2608.21402v1 Announce Type: cross Abstract: World action models (WAMs) jointly denoise future video frames and robot actions, and the video prior is expected to generalize their control. Camera...
arXiv:2610.09579v1 Announce Type: new Abstract: Trajectory optimisation for cone-beam computed tomography (CT) determines which information sparse-view scans acquire. Fixed candidate pools prevent of...
CalibSwitch is an observation‑driven framework for Camera–LiDAR perception that separates absolute extrinsic recovery from selective state maintenance. It introduces a cross‑modal absolute extrinsic generator (CAEG) that recovers full SE(3) candidates from image–point observations without needing an initial transform, and a selective recurrent calibration policy (SRCP) that decides when to update the working geometry based on observation quality and temporal history. On the nuScenes dataset, CAEG achieves mean translation and rotation errors of 0.248 m and 5.884°, while SRCP reduces composite error to 1.46 with only 9.70 % candidate commitments, improving frozen‑detector mAP and NDS by 1.43 and 0.92 points respectively.
The paper introduces a reliability‑aware framework for spacecraft pose estimation that integrates polarity–time localization, geometric recovery, event–CAD refinement, and trajectory optimization. It employs a three‑branch representation of positive, negative, and recent events, cross‑branch attention, and spatiotemporal aggregation, followed by a semantic‑point head for precision estimation. The system achieves a pose score of 0.0474 on the SPADES challenge, outperforming prior methods and demonstrating significant improvements through ablation studies.
TALON introduces Token‑Aligned Lightweight Adapters for 6‑DoF spacecraft pose estimation, inserting spatiotemporal 3D adapters before self‑attention layers of a frozen Vision Transformer. A patch‑token alignment loss grounds adapted features to keypoint structure, enabling the frozen backbone to reason over temporally enriched tokens with minimal added parameters. On the SPADES and SwissCube datasets, TALON cuts pose error by 50% and improves ADD‑0.1d accuracy by 21.8%, respectively, while also achieving significant gains in zero‑shot sim‑to‑real cross‑domain evaluation.
arXiv:2504.15776v2 Announce Type: replace Abstract: Public autonomous driving datasets underpin the training and benchmarking of perception, mapping, and localization algorithms, yet residual inaccur...
arXiv:2610.17521v1 Announce Type: cross Abstract: Evaluating VLA policies on real robots is costly, time-consuming, and difficult to reproduce, making real-to-sim simulation essential for scalable ev...
ALS boresight calibration has relied for two decades on dedicated flight patterns over structured scenes containing planar surfaces of varied aspect and slope. While reliable, this approach imposes constraints on the scene content and operations, which limits its applicability to boresight recovery within routine mapping missions.