14 May 2025

Autonomous Robotics Development in Robot Operating System (ROS) 2 Humble

Abstract: This report presents a novel Robot Operating System (ROS) 2–based simulation framework designed to facilitate the development and testing of an autonomous navigation stack. Elements of the navigation stack, including lidar odometry, simultaneous localization and mapping (SLAM), and frontier exploration, are discussed in detail. The key features of the navigation stack include real-time performance and scalable architecture. The simulation results were applied to a physical robot. As a result, the physical robot was able to autonomously map the interior of a building and to generate 2D occupancy and 3D point clouds of the environment.

14 May 2025

Robot Operating System Innovations in Autonomous Navigation

Abstract: This report presents the results of simulations conducted in preparation for the 2024 Maneuver Support and Protection Integration Experiments (MSPIX) demonstration. The study aimed to develop and test a system for autonomous navigation in complex environments using advanced algorithms to enable the robot to avoid obstacles and navigate safely and efficiently. The report describes the methodology used to develop and test the autonomous navigation system, including the use of simulation, to evaluate its performance. The results of the simulation tests are presented to highlight the effectiveness of the navigation solution.

7 Jan 2025

Exploring Lidar Odometry Within the Robot Operating System

Abstract: Here, we explore various lidar odometry approaches (with both 3 and 6 degrees of freedom) in simulation. We modified a virtual model of a TurtleBot3 robot to work with the various odometry approaches and evaluated each method within a gazebo simulation. The gazebo model was configured to generate an absolute ground truth for comparison to the odometry results. We used the evo package to compare the ground truth with the various lidar odometry values. The results for KISS-ICP and laser scan matcher (LSM), including two simultaneous localization and map-ping (SLAM) approaches, Fast Lidar-Inertial Odometry (FAST-LIO), and Direct Lidar Odometry (DLO), are provided and discussed. We also tested one of the approaches on our physical robot.

22 Jan 2024

Amphibious Uncrewed Ground Vehicle for Coastal Surfzone Survey

Abstract: The capability of a commercial off-the-shelf amphibious bottom crawling robot is explored for surveying seamless topography and bathymetry across the beachface, surfzone, and very nearshore. A real-time-kinematic (RTK) antenna on a mast was added to the robotic platform, a Bayonet-350 (previously the C2i SeaOx). Data collected from the robot were compared with those collected by the Coastal Research Amphibious Buggy (CRAB) and the Lighter Amphibious Resupply Cargo (LARC), unique amphibious vessels capable of collecting seamless topography and bathymetry in use for decades at the US Army Engineer Research and Development Center’s Field Research Facility (FRF). Data were compared on five different days in a range of wave conditions (Hs < 1 m in 8-m depth) resulting in a root-mean square difference of 8.7 cm and bias of 2 cm for 24 different cross-shore profile comparisons. Additionally, a repeatability test was performed to assess measurement uncertainty. The repeatability test indicated a total vertical uncertainty (TVU) of 5.8 cm, with the highest spatial error at the shoreline.