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Palabras clave – provistas por la editorial

differential GNSS; DBA; low-cost; combined positioning; multi-sensor fusion; visual point and line feature; SLAM; LiDAR-visual-inertial odometry; forest point cloud; Unmanned Aerial Vehicle (UAV); Terrestrial Laser Scanning (TLS); canopy cover; event camera; feature tracking; intensity/inertial integration; pseudorange positioning; branch and bound; nonlinear least squares; eLoran; trust region reflective algorithm; initialization; LiDAR-inertial odometry; point cloud registration; visual SLAM; instance segmentation; neural network; pose estimation; GNSS; IMU; urban positioning; fault detection and exclusion; LIDAR; coupling methods; mobile RTK; low-cost GNSS receiver; positioning accuracy; LiDAR data; tree characteristics; terrain conditions; precision forestry; TreeNet; geographic object-based approach; commercial forests; step detection; indoor positioning; unconstrained state; peak detectors; adaptive threshold; variable sliding window; visibility graph; computational geometry; path planning; mapping; tightly-coupled integration; LIDAR-inertial SLAM; rod-shaped and planar feature; sliding-window; graph optimization framework; INS/GNSS integrated navigation; CNN-GRU; CKF; GNSS outage; multi-GNSS; real-time kinematic; maximum correntropy criterion; Kalman filter; wide-lane; ionosphere-free; GNSS/INS; 3D LiDAR; fault detection; localization; integrity assessment; cooperation SLAM; multi robot system; UAV; UGV; map assistance; particle filter; global search algorithm; pedestrian navigation; Simultaneous Localization and Mapping; autonomous driving; high definition map