8 Sep 2026

Using the ERDC Wellbot to Prevent and Remediate Biochemical Fouling in Relief Wells

Abstract: Relief wells relieve subsurface hydrostatic pressures that may develop within the foundations of dams, levees, and hydraulic structures. When these wells become fouled, they can lose their ability to reduce the hydrostatic pressure around the structure, which compromises its safety. Current methods for addressing fouling in relief wells can be hazardous, labor-intensive, ineffective, and expensive. This study tested the effectiveness of the US Army Engineer Research and Development Center (ERDC) Wellbot, an autonomous device that integrates UVC-emitting lamps with brushes to facilitate both physical and chemical removal of biofilm and chemical scale on the interior screen and casing of a well. The Wellbot was tested in 19 relief wells at two dams. Results were mixed, with the Wellbot generally outperforming conventional cleaning methods in qualitative visual comparison, matching conventional treatment in water level reduction, and either matching or underperforming conventional treatment in producing a specific capacity improvement. The Wellbot was simple to operate by a single person, and no training or technical expertise was required. The study identified the need for an automatic shutoff function, which, once implemented, should ready the Wellbot for wider deployment across the US Army Corps of Engineer’s more than 225 dam and levee systems.

23 Sep 2025

Using the Robot Operating System for Uncrewed Surface Vehicle Navigation to Avoid Beaching

Abstract: Our research explores the use of the Robotic Operating System (ROS) to autonomously navigate an uncrewed surface vehicle (USV). As a proof of concept, we set up a simulated world and spawned a virtual Wave Adaptive Modular Vehicle (WAM-V). We used the robot_localization package to localize the WAM-V in the virtual world and used move_base for the navigation of waypoints. The move_base package used both costmaps and path planners to reach its intended goal while simultaneously avoiding sub-merged shallow-water obstacles. Shallow-water obstacles are obstacles at a depth that is less than a user-defined value (1 meter in this case). Finally, we investigated using vizanti as a mission planner. This report provides a detailed explanation of the parameters that were modified to demonstrate a successful proof of concept.

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.