arXiv Computer Vision
Hydra: Marker-Free RGB-D Hand-Eye Calibration
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arXiv Computer Vision
3d ago
DARP: A Calibrated Dual-Arm RGB-D-IR Dataset for Multi-View Robotic Perception
arXiv:2608.31002v1 Announce Type: cross Abstract: Robotic perception from a single viewpoint is often limited by self-occlusion and incomplete surface visibility. This paper presents DARP(Dual-Arm Ro...
arXiv AI
Jul 24
Robostral Navigate
arXiv:2607. 20785v1 Announce Type: cross Abstract: Deploying navigation systems at scale requires a recipe that minimizes sensor assumptions, generalizes across robot embodiments, and trains efficiently.
arXiv AI
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From Fixed to Free Cameras: Calibration-Free View-Robust Vision-Language-Action Model
arXiv:2607. 05396v1 Announce Type: cross Abstract: Real-world robot deployment rarely maintains the training-stage camera setup, where cameras often experience repositioning or remounting depending on actual scenarios.
arXiv Computer Vision
2d ago
MarUco: A Markerless 6D Pose Estimation Framework for Closed-Loop Control of Surgical Continuum Manipulators
arXiv:2602.16365v2 Announce Type: replace-cross Abstract: Flexible endoscopic continuum manipulators offer high dexterity and access to complex anatomy, but nonlinear hysteresis limits feedforward co...
Hugging Face Trending Papers
Jul 6
From Fixed to Free Cameras: Calibration-Free View-Robust Vision-Language-Action Model
Real-world robot deployment rarely maintains the training-stage camera setup, where cameras often experience repositioning or remounting depending on actual scenarios. Existing view-robust Vision-Language-Action (VLA) policies tolerate such camera variations only when the camera extrinsics are explicitly provided, making them fragile and hard to use especially when view robustness is critical.
arXiv Machine Learning
Aug 27
Minimalist Visual Inertial Odometry
The paper introduces a minimalist visual-inertial odometry system that uses only four downward-facing photodiodes with optical Gabor masks and an IMU to estimate motion for differential-drive robots. By jointly optimizing mask parameters and a Temporal Convolutional Network in a physically-grounded simulator, the model decodes speed from the photodiode signals and combines it with IMU angular speed to produce a continuous planar trajectory. Experiments on a prototype robot across indoor and outdoor terrains show that the system closely follows reference trajectories without real-world fine-tuning.