Search Results for "localization"

RTAB-Map (Real-Time Appearance-Based Mapping) is a RGB-D, Stereo and Lidar Graph-Based SLAM approach based on an incremental appearance-based loop closure detector. The loop closure detector uses a bag-of-words approach to determine how likely a new image comes from a previous location or a new location. When a loop closure hypothesis is accepted, a new constraint is added to the map’s graph, then a graph optimizer minimizes the errors in the map. A memory management approach is used to...

ROS 2 package of 3D lidar slam using ndt/gicp registration and pose-optimization. ros2 slam package of the frontend using OpenMP-boosted gicp/ndt scan matching and the backend using graph-based slam.

DLIO is a new lightweight LiDAR-inertial odometry algorithm with a novel coarse-to-fine approach in constructing continuous-time trajectories for precise motion correction. It features several algorithmic improvements over its predecessor, DLO, and was presented at the IEEE International Conference on Robotics and Automation (ICRA) in London, UK in 2023.

DLO is a lightweight and computationally efficient frontend LiDAR odometry solution with consistent and accurate localization. It features several algorithmic innovations that increase speed, accuracy, and robustness of pose estimation in perceptually challenging environments and has been extensively tested on aerial and legged robots. This work was part of NASA JPL Team CoSTAR's research and development efforts for the DARPA Subterranean Challenge, in which DLO was the primary state estimation component for our fleet of autonomous aerial vehicles.