Robuta

Sponsor of the Day: Jerkmate

https://arxiv.org/abs/2604.15864 [2604.15864] Environment-Adaptive Solid-State LiDAR-Inertial Odometry Abstract page for arXiv paper 2604.15864: Environment-Adaptive Solid-State LiDAR-Inertial Odometry solid state lidar environment adaptive inertial odometry 2604 https://arxiv.org/html/2604.15864v1 Environment-Adaptive Solid-State LiDAR-Inertial Odometry This work was supported by the National... solid state lidar environment adaptive inertial odometry work supported https://www.scirp.org/journal/paperinformation?paperid=149956 Adaptive Lidar-Inertial SLAM Algorithm with Multi-Feature Assistance in Degraded Environments To address the issues of feature mismatching and map overlap drift in simultaneous localization and mapping (SLAM) within degraded environments characterized... lidar inertial multi feature adaptive slam algorithm https://ieeexplore.ieee.org/document/9345356/ Unified Multi-Modal Landmark Tracking for Tightly Coupled Lidar-Visual-Inertial Odometry | IEEE... We present an efficient multi-sensor odometry system for mobile platforms that jointly optimizes visual, lidar, and inertial information within a single integra unified multi tightly coupled visual inertial modal landmark https://ieeexplore.ieee.org/document/10610460/ Tightly-Coupled LiDAR-Visual-Inertial SLAM and Large-Scale Volumetric Occupancy Mapping | IEEE... Autonomous navigation is one of the key requirements for every potential application of mobile robots in the real-world. Besides high-accuracy state estimation, visual inertial slam tightly coupled large scale lidar volumetric