AD Robotics – RVR Top Plate and Gantry Arm [Poster]
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Recent advancements in mobile robotics have displayed impressive capabilities in traversing and accessing areas that are inaccessible to humans either due to the characteristics of the environment or potential hazards. Furthermore, these advancements within the field of mobile robotics, more specifically uncrewed ground vehicles (UGVs), give the ability to potentially survey, observe, and map these inaccessible areas for humans. However, one of the most challenging areas to implement this technology is underground environments. The main challenge with implementing this technology in underground environments is the dependence on either GPS or RF communication for UGVs to navigate properly. Therefore, in order to properly demonstrate the mapping capabilities of the UGV this challenge must be resolved. The overall goal of this study is to demonstrate the mapping capabilities of a UGV while addressing this challenge and documenting the implementation and testing phase of the robot. The proposed solution to this challenge is to implement a SLAM algorithm onto the main computational device of the UGV utilizing the Robot Operating System (ROS). The algorithm is the open-source software package Slam Toolbox developed by Steve Macenski. Furthermore, the sllidar_ros2 package from Slamtec will be used to gather the lidar data from an A3M1 2D lidar. A separate program will be created to gather odometry information for our UGV robot. All of these software packages will run together in a Docker environment. Through working on this project I have developed a better understanding of the world of robotics/autonomous systems, especially with applications such as navigation and mapping. Furthermore, through this project, I have been given exposure to how research is conducted within a DOE lab setting. As robotics/autonomous systems become more advanced it's important to pursue more avenues of research such as this project as it will ensure the development of our capabilities.
The purpose of the husky A200 ground robot is to autonomously navigate through the places where it is very hazardous for human beings to reach and operate, like nuclear power plants, chemical industries. The aim is to navigate the ground robot autonomously with an Arm mounted on the robot along with the different sensors as camera, and Lidar. The autonomous motion of the robot is controlled by the controller which uses path planner for trajectory generation of the robot. The mission planner uses the current position of the husky A200, given the way points of the initial and the destination it would extract a best possible route based on the current events provided using GMapping. The global reference frame is used for planning the way points. Creating the appropriate path and the actions required to follow the path are given by the motion planner. The motion planner depends on the active sensor data such as obstacles, lanes, based on the sensor data feasible path is generated. Feasibility of the path is determined by the dynamics of the husky and a series of points generated with certain velocity and acceleration profile. The controller adjusts the lateral, longitudinal and yaw motion of the husky to command the behaviors. The kinematic model is developed for kinematic motion of the husky and the dynamic model is developed for transient and steady state characteristics. The images and other type of data captured by the camera are processed through the computational framework used to build machine learning models. TensorFlow will be used for deep learning and to identify and classify different objects around the husky. (authors)
Battery‐electric vehicles (EVs) are growing exponentially. The demand for these batteries is expected to increase sevenfold by 2035. The EV batteries reach their end of life when the capacity fades to 70%–80% of new, with some being removed from the primary applications with even lower levels of degradation. These batteries can be used in less demanding applications. The disassembly process is currently manual, slow, unsafe, and expensive. Automation is needed to increase the throughput. EV battery packs feature various continually changing designs and form factors, which limit the usefulness of deterministically programmed robotic solutions. The conceptual robotic disassembly of EV batteries has attracted the attention of researchers. However, while many approaches have been proposed, practical implementations are lacking. Here, we review proposed concepts for EV battery disassembly and describe the selected approach, with elements of partial solutions validated in a laboratory setting, including the selection of commercial solutions, the development of custom end effectors, and methodologies for detection, localization, and classification of fasteners. The computer vision tasks employed an overhead 2D camera to detect the type of battery pack and approximate localization of fasteners, and a 3D camera mounted on the robotic arm for precise localization (position and tilt) and classification.
The search for life beyond Earth necessitates a rigorous and comprehensive examination of biosignatures, the types of observable imprints that life produces. These imprints and our ability to detect them with advanced instrumentation hold the key to our understanding of the presence and abundance of life in the universe. Biosignatures are the chemical or physical features associated with past or present life and may include the distribution of elements and molecules, alone or in combination, as well as changes in structural components or physical processes that would be distinct from an abiotic background. The scientific and technical strategies used to search for life on other planets include those that can be conducted in situ to planetary bodies and those that could be observed remotely. Here this chapter discusses numerous strategies that can be employed to look for biosignatures directly on other planetary bodies using robotic exploration including those that have been deployed to other planetary bodies, are currently being developed for flight, or will become a critical technology on future missions. Search strategies for remote observations using current and planned ground-based and space-based telescopes are also described. Evidence from spectral absorption, emission, or transmission features can be used to search for remote biosignatures and technosignatures. Improving our understanding of biosignatures, their production, transformation, and preservation on Earth can enhance our search efforts to detect life on other planets.
SAND2021-15050 O Mantisa is an application programming interface (API) developed for a robotic hardware platform used to foster open collaboration with university partners. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.
This paper describes development and demonstration of remote crawling systems to support periodic examinations of interim dry storage system (DSS) canisters for spent nuclear fuel in the USA. Specifically, this work relates to robotic crawler developments for “canister” based DSS systems which form the majority population of DSSs, in the USA, for interim storage of spent nuclear fuel. Consideration of potential degradation of the welded stainless-steel canister in these systems is required for continued usage in the period of extended operation (PEO) beyond their initial licensed or certified terms. Challenges associated with performing the periodic examinations are associated with physical access to the canister surface which is constrained due to narrow annulus spaces between the canister and the overpack, tortuous entry pathways, and high temperatures and radiation doses that can be damaging to materials and electronics. Motivations for performing periodic examinations and developing robotic crawlers for performing those examinations remotely will be presented and several activities to demonstrate robotic crawlers for different DSS systems are summarized.
Production of three-dimensional metallic parts through integration of an articulated robot and gas metal arc welding, also known as wire arc additive manufacturing (WAAM), can produce large-scale components with moderate geometrical complexity. This technology is particularly appealing due to its high deposition rates, scalability, and cost-effective feedstock compared to other AM processes. Despite its advantages, WAAM adoption is hindered by challenges in ensuring geometric conformity without extensive distortion, defect-free structures, and consistent mechanical properties. Finite element analysis (FEA) is often used to address the challenge of geometrical conformity. As the size of parts increases, the best practices for mesh size and temporal resolution known in the literature become computationally unviable. This research examined the effects of mesh and time-step resolutions during transient FEA of a large-scale (248 layers) metallic part. The impact of computational parameters on the thermal history, displacement, and residual stress distributions were evaluated. The results showed that predicted distortion was consistent across resolutions, while time-step length significantly affected predicted thermal history, and mesh size influenced residual stress distributions. To investigate this relationship further, directionally biased meshes were considered and analyzed. The results indicated that increasing mesh resolution perpendicular to the welding path yielded stress predictions that aligned closely with higher-resolution models while offering substantial computational savings. In conclusion, the significances of this research are related to verification and validation of WAAM models for widespread industrial adoption and pragmatic guidelines for optimizing computation parameters for balancing computational efficiency and predictive accuracy of residual stress and distortion.
In 2017, the DOE Environmental Management Office of Technology Development (DOE-EM TD) sponsored the H-Canyon Advanced Technology Demonstration (ATD) to demonstrate to DOE facilities the value of using new commercial-off-the-shelf (COTS) and near-ready technologies to solve difficult problems and enhance worker safety. The DOE Savannah River Site (SRS) H-Canyon Air Exhaust Tunnel (HCAEX) inspection task was identified as representative of the hazardous, human denied environments which could benefit from advanced technologies. The HCAEX underground concrete tunnel is visually inspected biannually using a camera mounted on a remotely operated vehicle (ROV) designed and built by SRNL. While tunnel images have provided valuable visual information, it is desirable to have a higher order of understanding of the environment to support a more thorough structural integrity (SI) analysis and for long term planning purposes. As part of the ATD, the Concrete Integrated Product Team (CIPT) was formed to identify and evaluate available sensors and methods mature enough to remotely obtain tunnel concrete characterization data of high value and with a high probability of success. The team included SMEs and H-Canyon stakeholders in the field of concrete, nondestructive examination (NDE), structural integrity, sensors and remote systems from SRNL, SRNS, LANL, DOE-SR and the Army Corps of Engineering. The CIPT completed an in-depth identification of customer concrete inspection needs and potential technology solutions. Sensors and methods were evaluated on performance, data usefulness, cost and the feasibility of a successful deployment given the unique tunnel access challenges and environment. Two technologies were identified as promising by the CIPT for near term demonstration and evaluation: Lidar (Light Detection and Ranging) 3-dimensional (3D) mapping and remote robotic deployment of NDE instrumentation. Laser spectroscopy to characterize tunnel surface chemical changes was also of interest, but presently cost prohibitive. This paper will include a discussion of the two efforts underway to evaluate and implement the CIPT recommendations. First, the status of the November 2019 deployment of Lidar at a single location into the tunnel is presented. This initial deployment provided the team a learning curve and lessons learned on the challenges of tunnel deployment to include remote operation and data collection, stabilization of the sensor in high air flow (∼30 mph), ability to achieve a tolerance accuracy of 0.25-inches, and the probability to identify change in tunnel dimensions over time. Secondly, a discussion on the development of the Robotic Arm Concrete Inspection Test Bed capable of deploying NDE instruments to examine custom concrete forms will be presented. Concrete forms simulating the rough concrete surfaces, strength, composition and potential structural defects that can be found at our DOE EM facilities have been designed and built for the test bed. Two state-of-the art concrete NDE instruments have been identified as having potential to work on rough concrete walls, they are being tested and characterized as to their ability to provide desired structural integrity data to include wall thickness and defect identification on the developed test beams. Lastly, lessons learned, and the path forward will be presented. (authors)
The 27 in-service double-shell tank (DST) systems at Hanford provide interim storage for nearly 56 million gallons of nuclear and hazardous chemical legacy waste. The safe and reliable storage of the waste is critical to the site's extended cleanup mission. While in service, the leak integrity of the DSTs must be demonstrated to satisfy the Washington Administrative Code, inform decisions on tank management, and gauge fitness for continued service beyond originally intended design lives. The carbon steel plates and welds that comprise DST primary tank sidewalls and lower knuckles are routinely 'sampled' for volumetric non-destructive testing using ultrasonic inspection technology to determine whether corrosion pitting, cracking, or general corrosion are occurring that could compromise tank leak integrity. However, the carbon steel plates and welds that comprise the bottoms of primary tanks have not been thoroughly inspected since the DSTs were constructed (i.e., since 1968-1986) due to limited physical access to the exterior tank bottoms. The Robotic Air-slot Volumetric Inspection System, or 'RAVIS,' is being engineered to overcome the challenge of tank bottom in-service inspection. The system will be deployed under primary tanks within the small cooling channels/air-slots in the refractory pads upon which the tanks rest and will use ultrasonic guided wave inspection technology to volumetrically inspect physically inaccessible regions that make up ∼90% of a tank bottom, as well as regions that are physically accessible from the air-slots but comprise only ∼10% of a tank bottom. This paper describes the air-slot sensor and robotic deployment system and focuses on the testing approach and methods that are being applied to support (1) design feedback and performance acceptance (requirement verification) and (2) performance repeatability/reliability assessments (qualification) to ensure the RAVIS is prepared for successful inservice inspections of primary tank bottoms. Test progress made against the test plan, the results of 2019 testing, and the future outlook are included. (authors)
Mars exploration motivates the search for extraterrestrial life, the development of space technologies, and the design of human missions and habitations. Here, we seek new insights and pose unresolved questions relating to the natural history of Mars, habitability, robotic and human exploration, planetary protection, and the impacts on human society.
Date of collection: May 18, 2023 Location: State Street, Chicago, IL This data set contains lidar and vision data collected along State Street. The vehicle started from outside of the McCormick Tribune Campus Center at the Illinois Institute of Technology’s Mies Campus and headed north along State Street, until the north end of State Street in the Gold Coast. The data contains the following Robot Operating System (ROS) topics: - /Central_Camera_blurred – Image flow from coaxial camera heading, vehicle front. - /Left_Camera_blurred – Image flow from left camera, 60° from central camera on the left side. - /Right_Camera_blurred – Image flow from right camera, 60° from central camera on the right side. - /camera0/camera_info – Intrinsic and distortion information of left camera. - /camera0/projection_matrix – Extrinsic matrix of left camera from lidar. - /camera2/camera_info – Intrinsic and distortion information of central camera. - /camera2/projection_matrix – Extrinsic matrix of central camera from lidar. - /camera5/camera_info – Intrinsic and distortion information of right camera. - /camera5/projection_matrix – Extrinsic matrix of right camera from lidar. - /novatel/oem7/bestpos – Latitude, longitude, and elevation information from NovAtel GNSS-INS system. - /points_raw – VLP-32 lidar point cloud. - /tf – Vehicle base frame. The data are organized into a data description file and one or more ROS .bag files, dependent on original file size. The data description file provides information about the data collection date, location, and detailed mapping, while the .bag file(s) contain the actual data. Please note that for the purpose of securing personally identifiable information, all license plates and faces included in this publication have been intentionally blurred during real-time processing. 
Sunny is a Julia package designed to serve the needs of the quantum magnetism community. It supports the specification of a very broad class of spin models and a diverse suite of numerical solvers. These include powerful methods for simulating spin dynamics both in and out of equilibrium. Uniquely, it features a broad generalization of classical and semiclassical approaches to SU(N) coherent states, which is useful for studying systems exhibiting strong spin-orbit coupling or local entanglement effects. Sunny also offers a well-developed framework for calculating the dynamical spin structure factor, enabling direct comparison with scattering experiments. Ease of use is a priority, with tools for symmetry-guided modeling and interactive visualization.
When characterizing facilities, advanced autonomous systems are safe, efficient, and cost-effective tools, which can safely deploy state-of-the-art instrumentation without exposing workers to radiation risks. One main focus of the research is the visual mapping of the environment.This paper presents a framework for the mapping aspect that utilizes lidar and SLAM technologies coupled with a monocular camera to create a point cloud of the environment. Upon completion, the present research work aims to provide an autonomous mobile robot the capability to localize itself and aid the user with visualizing the radiation data. Challenges: C++ node needs to properly synchronize image and point cloud data. 3D lidar has resolution of ± 3 cm. Proper camera calibration needed. Transforms need to be precise for proper alignment of image and point-cloud. Results: Voxelated point clouds. Accurate colors from calibrated cameras including details smaller than lidar resolution. Developed Robotics Operating System (ROS) package for ease of transfer to other robot platforms.
A pressing need for the Double-Shell Tank Integrity Program at Hanford is of the ability to inspect the bottom of the tanks. Though the DSTs' annulus spaces (the space between the internal and external tank walls) have been inspected visually since 1992 and with Ultrasonic Testing (UT) since 1996, inspections of the tank bottoms have been able to be conducted due to limitations of available technology, omitting about 40 percent of the tank surface below the maximum fill level from routine inspection. Visual inspections of the tank annulus have been conducted up to five times in some DSTs and portions of the annulus space for all of the DSTs has been inspected twice with UT. This region includes the walls of the primary tank and secondary liner along with accessible portions of the secondary liner bottom. Due to this lack of technology, the degradation of the primary tank bottom in Tank AY-102 was undetected until the tank leaked into its annulus space, confirmed in 2012. Since that time, WRPS has been working with the nondestructive examination community and the Pacific Northwest National Laboratory, to evaluate potential technologies to conduct these challenging remote inspections. Recent work has included the development, testing, and deployment of several remote visual inspection technologies to observe the condition of the primary tank bottom of the DSTs by leveraging air distribution slots in the refractory pad on which it rests. Robotic solutions to conduct this inspection were developed with a detailed understanding of the physical configuration and operational logistics. Understanding and subsequent communication of these details to vendors within the robotics and nondestructive examination community was a critical component to the successful production of these new tools. Throughout the FY16-FY18 years, vendors from nondestructive examination community were solicited for ideas to meet the tank bottom inspection challenge. Two tank bottom visual inspection solutions were then pursued to meet that challenge. Both tools were successfully deployed at Tank AP-107, and provided valuable visuals, never before obtained from the under tank environment of a double-shell tank. While there are minor opportunities for improvement identified with each system, general outcomes were overwhelmingly positive. Both systems were successfully able to navigate the refractory air slot pattern from the outer edge to the tank center and record video footage. The micro-crawler provided high quality and very stable footage through the air slot pattern, but took longer to deploy into the slots and traverse through them than the alternative system. The push-pull tethered camera was able to navigate all seven of its target air slots in a matter of a few hours, which included deployment, movement between slot entrances, and complete removal of the system from the annulus environment. Through these air slots, new information was gained about the tank bottom and refractory pad condition of tank AP-107, AP-106, AP-108, and AN-102. While some debris was noted in the air slots, including sand, chipped refractory, and construction materials, the refractory was found to be structurally stable and adequately supporting the primary tank bottom through the full diameter of the tank. Primary tank bottom steel exterior was found to be in good condition, free of ongoing or aggressive corrosion conditions. Looking toward the future, robotic access to and visual inspection of refractory air slots and the primary tank bottom steel has now proven viable. Incorporating periodic air slot inspections as a regular practice within the Double-Shell Tank Integrity Program is the next step, allowing trending of any changes in condition. As ultrasonic testing infrastructure was leveraged to complete the initial system deployments described in this report, it makes sense to adopt that same strategy for ongoing periodic examinations and deploy these primary tank bottom inspection tools alongside ultrasonic testing operations. Development of visual inspection tools to evaluate the primary tank bottom region of the double-shell tanks was planned as the first stage of inspection. Continued development of volumetric sensors and incorporation of these inspection tools into Hanford's ongoing Double-Shell Tank Integrity Program are the next steps, seeking to continuously expand understanding of asset integrity and remaining useful life. (authors)
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In this white paper, we present the MegaMapper concept. The MegaMapper is a proposed ground-based experiment to measure Inflation parameters and Dark Energy from galaxy redshifts at $2 < z < 5$. In order to achieve path-breaking results with a mid-scale investment, the MegaMapper combines existing technologies for critical path elements and pushes innovative development in other design areas. To this aim, we envision a 6.5-m Magellan-like telescope, with a newly designed wide field, coupled with DESI spectrographs, and small-pitch robots to achieve multiplexing of at least 26,000. This will match the expected achievable target density in the redshift range of interest and provide a 10x capability over the existing state-of the art, without a 10x increase in project budget.