התחברות
תובנה - Robotics Localization
Leveraging Semi-Supervised Novelty Detection to Enhance Ultra-Wideband Localization Reliability in Dynamic Environments
This work proposes a semi-supervised novelty detection methodology to precisely characterize and predict Ultra-Wideband (UWB) error within a specific environment, enabling reliable robot localization in dynamic settings.
Resource-Aware Collaborative Monte Carlo Localization with Efficient Distribution Compression
A novel resource-aware approach for collaborative global localization that reduces the amount of information exchanged and the computational cost, while improving localization performance.
Multi-Agent Ultra-Wideband Relative Pose Estimation with Constrained Communications in 3D Environments
A novel 3D relative pose estimation system that uses only locally collected UWB range measurements, a priori state constraints, and event-based detections of constraint violations, without the need for continuously transmitted measurements.
אודות
מוצרים | משאבים
© 2024 by Linnk AI