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The LiDAR and inertial sensors based localization and mapping are of greatsignificance for Unmanned Ground Vehicle related applications. In this work, wehave developed an improved LiDAR-inertial localization and mapping system forunmanned ground vehicles, which is appropriate for versatile search and rescueapplications. Compared with existing LiDAR-based localization and mappingsystems such as LOAM, we have two major contributions: the first is theimprovement of the robustness of particle swarm filter-based LiDAR SLAM, whilethe second is the loop closure methods developed for global optimization toimprove the localization accuracy of the whole system. We demonstrate byexperiments that the accuracy and robustness of the LiDAR SLAM system are bothimproved. Finally, we have done systematic experimental tests at the Hong Kongscience park as well as other indoor or outdoor real complicated testingcircumstances, which demonstrates the effectiveness and efficiency of ourapproach. It is demonstrated that our system has high accuracy, robustness, aswell as efficiency. Our system is of great importance to the localization andmapping of the unmanned ground vehicle in an unknown environment.

An Enhanced LiDAR-Inertial SLAM System for Robotics Localization and Mapping