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Category: Publications: Geospatial Research Laboratory (GRL)
  • Mapping and Localization Within a Mock Sewer System

    Abstract: Herein, we explored a robot’s ability to localize and map, both in simulation and on a physical robot, within a mock sewer system. Mapping and localization techniques were first developed and tested in simulation and were then transitioned to the actual robot for additional physical testing. Several odometry and simultaneous localization and mapping (SLAM) techniques, including gmapping, SLAM toolbox, elevation mapping, and RTABMap, were evaluated for this particular environment. The results of the odometry and the various SLAM approaches are discussed in detail.
  • UGV SLAM Payload for Low-Visibility Environments

    Abstract: Herein, we explore using a low size, weight, power, and cost unmanned ground vehicle payload designed specifically for low-visibility environments. The proposed payload simultaneously localizes and maps in GPS-denied environments via waypoint navigation. This solution utilizes a diverse sensor payload that includes wheel encoders, inertial measurement unit, 3D lidar, 3D ultrasonic sensors, and thermal cameras. Furthermore, the resulting 3D point cloud was compared against a survey-grade lidar.
  • Unmanned Ground Vehicle (UGV) Full Coverage Planning with Negative Obstacles

    Abstract: We explored approaches that offer full coverage path planning while simultaneously avoiding negative obstacles. These approaches are specific to unmanned ground vehicles (UGVs), which need to constantly interact with a traversable ground surface. We tested multiple potential solutions in simulation, and the results are presented herein. Full coverage path planner (FCPP) approaches were evaluated based on their ability to discretize their paths, use waypoints effectively, and be easily integrated with our current robot platform. For negative obstacles, we explored approaches that will integrate with our current navigation stack. The preferred solution will allow for teleoperation, waypoint navigation, and full autonomy while avoiding positive and negative obstacles
  • Unmanned Ground Vehicle (UGV) Path Planning in 2.5D and 3D

    Abstract: Herein, we explored path planning in 2.5D and 3D for unmanned ground vehicle (UGV) applications. For real-time 2.5D navigation, we investigated generating 2.5D occupancy grids using either elevation or traversability to determine path costs. Compared to elevation, traversability, which used a layered approach generated from surface normals, was more robust for the tested environments. A layered approached was also used for 3D path planning. While it was possible to use the 3D approach in real time, the time required to generate 3D meshes meant that the only way to effectively path plan was to use a preexisting point cloud environment. As a result, we explored generating 3D meshes from a variety of sources, including handheld sensors, UGVs, UAVs, and aerial lidar.
  • Docker Containers and Images for Robot Operating System (ROS)–Based Applications

    Abstract: Docker is a tool designed to make it easier to create, deploy, and run applications by using containers. Containers allow a developer to package and ship out an application with all of the parts it needs, such as libraries and other dependencies. Herein, we investigate using a Docker image to deploy and run our Robot Operating System (ROS)–based payload on a robot platform. Ultimately, this would allow us to quickly and efficiently deploy our payload on multiple platforms.
  • 3D Mapping and Navigation Using MOVEit

    Abstract: Until recently, our focus has been primarily on the development of a low SWAP-C payload for deployment on a UGV that leverages 2D mapping and navigation. Due to these efforts, we are able to autonomously map and navigate very well within flat indoor environments. This report will explore the implementation of 3D mapping and navigation to allow unmanned vehicles to operate on a variety of terrains, both indoor and outdoor. The method we followed uses MOVEit, a motion planning framework. The MOVEit application is typically used in the control of robotic arms or manipulators, but its handling of 3D perception using OctoMaps makes it a promising software for robots in general. The challenges of using MOVEit outside of its intended use case of manipulators are discussed in this report.
  • Application of a Satellite-Retrieved Sheltering Parameterization (v1.0) for Dust Event Simulation with WRF-Chem v4.1

    Abstract: Roughness features (e.g., rocks, vegetation, furrows) that attenuate wind flow over the soil surface can affect the magnitude and distribution of sediment transport in aeolian environments. Existing transport models often rely on vegetation attributes derived from static land use datasets or remotely sensed greenness indicators to incorporate sheltering effects on simulated particle mobilization. These approaches do not represent the 3D nature or spatiotemporal changes of roughness element sheltering and ignore the sheltering contribution of nonvegetation roughness features and brown vegetation common to dryland environments. We used an albedo-based sheltering parameterization in a dust transport modeling application of the Weather Research and Forecasting model with Chemistry (WRF-Chem). This method estimates sheltering effects on surface wind friction speeds and dust entrainment from the shadows cast by subgrid-scale roughness elements. We applied the albedo-derived drag partition to the Air Force Weather Agency (AFWA) dust emission module and studied simulated PM10 concentrations using the Goddard Global Ozone Chemistry Aerosol Radiation and Transport (GOCART) model as implemented in WRF-Chem v4.1. Our results demonstrate how dust transport simulation and forecasting with the AFWA dust module can be improved in vegetated drylands by calculating dust emission flux with surface wind friction speed from a drag partition treatment.
  • Three-Dimensional Geospatial Product Generation from Tactical Sources, Co-Registration Assessment, and Considerations

    Abstract: According to Army Multi-Domain Operations (MDO) doctrine, generating timely, accurate, and exploitable geospatial products from tactical platforms is a critical capability to meet threats. The US Army Corps of Engineers, Engineer Research and Development Center, Geospatial Research Laboratory (ERDC-GRL) is carrying out 6.2 research to facilitate the creation of three-dimensional (3D) products from tactical sensors to include full-motion video, framing cameras, and sensors integrated on small Unmanned Aerial Systems (sUAS). This report describes an ERDC-GRL processing pipeline comprising custom code, open-source software, and commercial off-the-shelf (COTS) tools to geospatially rectify tactical imagery to authoritative foundation sources. Four datasets from different sensors and locations were processed against National Geospatial-Intelligence Agency–supplied foundation data. Results showed that the co-registration of tactical drone data to reference foundation varied from 0.34 m to 0.75 m, exceeding the accuracy objective of 1 m described in briefings presented to Army Futures Command (AFC) and the Assistant Security of the Army for Acquisition, Logistics and Technology (ASA(ALT)). A discussion summarizes the results, describes steps to address processing gaps, and considers future efforts to optimize the pipeline for generation of geospatial data for specific end-user devices and tactical applications.
  • Establishing a Series of Dust Event Case Studies for North Africa

    Abstract: Dust aerosols often create hazardous air quality conditions that affect human health, visibility, agriculture, and communication in various parts of the world. While substantial progress has been made in dust-event simulation and hazard mitigation over the last several decades, accurately forecasting the spatial and temporal variability of dust emissions continues to be a challenge. This report documents an analysis of atmospheric conditions for a series of dust events in North Africa. The researchers highlight four analyzed events that occurred between January 2016 to present in the following locations: (1) the western Sahara Desert; (2) East Algeria and the Iberian Peninsula; (3) Chad-Bodélé Depression; (4) Algeria and Morocco. For each event, the researchers developed an overview of the general synoptic, mesoscale, and local environmental forcing conditions that controlled the event evolution and used a combination of available lidar data, surface weather observations, upper-air soundings, aerosol optical depth, and satellite imagery to characterize the dust conditions. These assessments will support downstream forecast model evaluation and sensitivity testing; however, the researchers also encourage broader use of these assessments as reference case studies for dust transport, air quality modeling, remote sensing, soil erosion, and land management research applications.
  • The DEM Breakline and Differencing Analysis Tool—Step-by-Step Workflows and Procedures for Effective Gridded DEM Analysis

    Abstract: The DEM Breakline and Differencing Analysis Tool is the result of a multi-year research effort in the analysis of digital elevation models (DEMs) and the extraction of features associated with breaklines identified on the DEM by numerical analysis. Developed in the ENVI/IDL image processing application, the tool is designed to serve as an aid to research in the investigation of DEMs by taking advantage of local variation in the height. A set of specific workflow exercises is described as applied to a diverse set of four sample DEMs. These workflows instruct the user in applying the tool to extract and analyze features associated with terrain, vegetative canopy, and built structures. Optimal processing parameter choices, subject to user modification, are provided along with sufficient explanation to train the user in elevation model analysis through the creation of customized output overlays.