Robotics and Sensor-Based Localization
This cluster of papers focuses on Simultaneous Localization and Mapping (SLAM) techniques, including visual odometry, 3D mapping, and graph optimization for mobile robots and autonomous systems. It covers various aspects such as monocular SLAM, RGB-D cameras, point cloud processing, and real-time implementation for accurate localization and mapping.
Papers listed on taxonomy pages are the top few works per node from the OpenAlex snapshot. That list is not exhaustive and is not an endorsement. The topic map and the journal registry remain separate: there is still no authoritative topic-to-venue or topic-to-organization edge. Search is a lexical lookup, not a claim that a venue publishes a topic.
Most cited
- Distinctive Image Features from Scale-Invariant Keypoints
- A method for registration of 3-D shapes
- Vision meets robotics: The KITTI dataset
- ORB-SLAM: A Versatile and Accurate Monocular SLAM System
- ORB-SLAM2: An Open-Source SLAM System for Monocular, Stereo, and RGB-D Cameras
- VINS-Mono: A Robust and Versatile Monocular Visual-Inertial State Estimator
Most recent
- MAC1toK: relax feature matching with maximal cliques for 3D registration
- CBAM-YOLOv11 and Geometric Constraint-Enhanced PnP for High-Precision EV Charging Port Pose Estimation
- Robust indoor automated guided vehicle navigation for logistics applications via imitation-augmented hierarchical reinforcement learning with a memory-attention generalized network
- Pose estimation using junction classification in monocular vSLAM
- Odometry and Mapping for Complex Environment Perception Under Partial-View Sensing
- Bio-Inspired Perception–Memory Coupling for Robust LiDAR–Inertial Odometry in Dynamic Environments