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At least 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Glovebox Handling of High-Consequence Materials with Super Baxter and Gesture-Based Programming - 18598

The handling of high-consequence materials is a difficult task requiring safe object manipulation while avoiding the risk of contamination or spillage. Specific operations including opening containers, segregating the wastes, and repackaging are required to be safely executed inside contained spaces such as gloveboxes. However, the workers' ability and dexterity to manipulate objects through thick protective gloves are compromised in many aspects. The fixed position of the glovebox arm ports restricts the movements of the workers' arms, which also makes it hard to lift heavy objects. Further, the operational workspace inside the glovebox is restricted by the gloves' reachability. Safety of workers is the paramount concern in glovebox operations and the very reason for their existence. Sharp edges and tools increases the risk of glove punctures, which may expose the operator to chemicals and radiation and risks contamination in the vicinity outside the glovebox. The operators are also affected by ergonomic stressors due to prolonged and repetitive operations. To achieve a high degree of human safety, robotic solutions to handle high-consequence materials inside the glovebox are desirable, as they remove the operators from the hazards listed above. However, robots, in general, lack the degree of adaptability necessary for most high-consequence material handling tasks as these tasks are often unstructured or highly variable. Likewise, most human operators, while highly skilled in the tasks at hand (task expertise), lack the robot programming skills necessary to adapt the robot's motions to the variations (programming expertise). A way to bridge this divide is to make robot programming more intuitive to human operators. Since humans naturally teach one another through demonstration and learning, robotic 'programming by demonstration' paradigms have begun to appear to reduce the burden of robot reprogramming. Gesture-Based Programming attempts to achieve that by enabling a robot to observe the normal actions and affordances of a human performing a task to learn to map those onto the skills of the robot. In the end, this approach permits benefits from both the human and the robot: the human's adaptive decision making and the robot's resilience to high-consequence material. Robotic solutions assuringly provide protection for the operators, however their autonomy brings about other potential risks. Artificial Intelligence is not perfect; it is a black box, which can produce results, but the full extent of those results may not be known precisely. In self-driving cars, a hypothetical AI problem is the 'green man detector'. Since self-driving cars have presumably never seen a green man, how can we know it won't veer toward him the first time it sees a green man? Likewise, even though GbP provides an open method for safe task execution replicating a human, incorrect task inferences can lead to potential collisions or unintended operations. Thus, a hardware safety measure is proposed to provide reliable operation inside the glovebox, and true safe operations are achieved by mechanically limiting the operational range of each arm link. The operational range is computed and validated through exhaustive offline simulations, which can be streamlined by affordable computing power. Super Baxter is one such robot which incorporates these capabilities. It is a human-like, bimanual robot, being developed at the Collaborative Robotics Lab (CRL) in conjunction with the Dept. of Energy/Environmental Management, Rethink Robotics, Barrett Technology, and the NSF Center for Robots and Sensors for the Human Well-Being (RoSe-HUB). Super Baxter is envisioned to represent the next generation of collaborative robots that will be intrinsically human-safe, as well as exceptionally human-intuitive. In summary, Super Baxter will enable safe glovebox operations through low-shot Gesture based Programming incorporated with hardware safety measures. Two aspects of safety will be discussed in the paper. First, the safety of the operator achieved by allowing him to program Super Baxter remotely through Gesture based Programming. Second, the safety of the glovebox, achieved by incorporating hardware safety measures using joint limits. Further, the capability of Super Baxter on Gesture based Programming is demonstrated through typical object manipulation tasks in glovebox operations. (authors)

42 ENGINEERING↗
DOE OSTI2016

Remote Retrieval, Disruption and Processing of Legacy Nuclear Waste - 16179

The UK National Nuclear Laboratory (NNL) is currently undertaking, in conjunction with Sellafield Ltd, a series of high profile trials of robotic equipment on a full scale test facility at their Workington Laboratory in England. These trials are designed to underpin and substantiate the processes proposed for the remote retrieval, disruption and processing of legacy Miscellaneous Beta Gamma Waste (MBGW) from a number of different donor plants on the Sellafield site, including some of the older fuel storage ponds and storage silos. These processes will be conducted inside the new Box Encapsulation Plant (BEP) which is due to be commissioned at Sellafield by 2020. These processes will subsequently enable Sellafield Ltd to safely recover legacy Intermediate Level Waste (ILW) from the older storage facilities on site and process it into a safer form which is more suitable for long term storage and then ultimately final disposal in a Geological Disposal Facility. As part of this legacy waste processing within the BEP plant, MBGW waste items will have to be remotely removed from a variety of different types of import skips. This waste will then be transferred, using robots, into the export container, which is a 3 m{sup 3} box liner, where the processed waste will be flood grouted to produce an encapsulated waste package. As part of this processing, any MBGW items consisting of sealed containers will have to be remotely disrupted before being grout encapsulated. This disruption is in order to (a) release any trapped liquors or gases from the containers and (b) ensure full grout infiltration of the container contents, thus minimising the amount of free liquors and voids within the final waste product. The NNL are conducting this technical work to confirm the viability of the proposed concept, processes and equipment. The developed solution consists of a linear layout of processing equipment with a pair of heavy duty, standard industrial, 'commercially off the shelf' (COTS) robots positioned around a Waste Handling Table. These robots have a 500 kg payload capacity and are operated remotely to handle all of the various types of MBGW waste, including the heavy and bulky items. The robots can be operated in manual tele-operation mode as well as pre-programmed automatic mode and have a range of primary and secondary tooling in order to perform the waste processing and disruption tasks as well as undertake general house-keeping and cleaning duties within the cell. The main tools include two types of hydraulic grab for the main waste recovery and handling tasks and a hydraulic shear for the waste disruption activities, but a number of other tools have also been designed and built for ancillary activities, such as a set of general purpose gripper jaws, drilling tool, bolt removal tool, pump tool, spray tool and a number of different housekeeping tools etc. The robot trials were started in November 2014, and have attracted a significant degree of high level stakeholder interest, including the UK Nuclear Decommissioning Authority (NDA), Office for Nuclear Regulation (ONR), Environment Agency (EA) and Radioactive Waste Management Limited (RWML) witnessing a number of the critical demonstration trials. Robots of the type selected are readily available, robust, reliable and easy to use. The trials have been very successful in proving the retrieval, processing and disruption operations, reducing the burden in the legacy waste facilities. Utilising robots to perform these tasks will lower the probability of producing non-compliant waste packages. In addition the robots can increase the consolidation of incoming waste skips into outgoing 3 m{sup 3} box liners, significantly increasing packing efficiencies and reducing the overall number of export containers produced thus lowering the decommissioning and waste storage/disposal costs. The trials have also enabled an assessment of the optimum way to operate the robots, as well as their reliability and maintainability issues. Engineering work associated with recovering failed robots and removing them from a typical Sellafield plant environment and then subsequently replacing them with functioning robots has also been undertaken and further work is now planned. The success of the trials, completed safely to a very challenging timescale, has enabled the use of robots in BEP to be endorsed as a viable option by the key stakeholders. Following a robust decision making process, this was a clear cut decision. The technical development and testing of the robot technology is currently continuing in order to investigate areas such as robot reliability, failure recoveries, human factors, ease of waste identification, optimisation of throughput rates, nuclearisation modifications etc. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2019

Informative Path Planning for Mapping Radiation

This project involves making measurements of contaminated areas using portable radiation detectors and small robots. Tasks involve operating detectors and small robots, combining data acquisition for the two systems, and automating the systems. The end result is a radiation map of contamination areas. Localization of radioactive sources and mapping of contamination distribution is essential when responding to emergencies, or when dealing with cleanup efforts. Radiation maps are used for situational awareness and for establishing a safe perimeter. However, it may be hazardous or impossible for humans to safely enter the site and survey the area. Informative Path Planning (IPP) is used to design a path for a robotic sensor platform to gather the most information about the radiation distribution while operating under the set of constraints given by the dynamics of the robot and other requirements such as minimizing the overall mission time. The key challenge for IPP is the tight coupling in multiple layers of decisions: Selection of locations to visit; Allocation of sensors to those locations; Processing of information gathered. Given a robot equipped with a basic gamma detector and Lidar sensor, how can we efficiently explore an unknown environment in such a way that we can satisfy the robot's constraints while simultaneously maximizing the accuracy of the map and minimizing the total runtime? This work presents a systematic procedure for IPP and environmental mapping that: Selects the best locations at which to sample; Finds the best path for robots; Estimates the measurement value at unknown locations using a Gaussian Process regression framework. Given a set of points where radiation measurements were taken, we are utilizing a Gaussian Process Regression with a Matern kernel to reconstruct the shape of the underlying ground truth. Mapping is done via the Robot Operating System's OpenSlam Gmapping package, which creates a 2D occupancy grid map. Simulated trials were run with a radiation source placed at random locations, and allowing the robot to select and move towards 20 samples at separate locations, as well as sampling along the path while moving. The simulated sensor model assumed an efficiency of 0.3, collection time of 1 second. Various weighting schemes were tested and compared. Quantitative evaluations often favored exploitation-heavy weighting schemes where μ was emphasized, with the Root Mean Squared Error (RMSE) quickly tending towards 2, whereas qualitative comparisons would favor exploration-biased schemes with greater weight on σ. The difference comes from operators often favoring knowing the general location of a source, rather than the exact properties of a source. Weighting of the path-length π often reduced the quality of the regression as less exploration occurred, however this may be deemed a worthwhile trade-off under certain circumstances, such as with sensitive robots. Successfully developed a methodology for informative path-planning for a robot to efficiently gather information and create a map of radiation. In the future, we would like to focus on: Hardware trials with integration of the robot platform and the IPP software; More refined sensor and environmental modeling; Multiple robot platforms.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Radioactive Source Localization via Bayesian Particle Filter

In the event of a misplaced radioactive source or other emergency situation, measuring a radiation field, mapping its distribution, and determining a source location are essential tasks to ameliorating the situation. However, radiation fields may be extremely hazardous to human surveyors and minimizing received radiation doses is just as essential. Robots appear to be a potential solution to these problems. Beyond simply measuring radiation, the robot's computer processing capabilities offer a way to apply complex data analysis methods to radiation measurements in real-time. Methods which predict likely source locations can then feed this information into other processes, potentially improving path planning and enabling more efficient measurements. Given a robot mounted with a gamma-ray detector, can we: develop a methodology to account for detector performance across a wide range of source angles, distances, and photon energies? operate an autonomously navigating robot to effectively survey and characterize an area of interest? implement a data analysis method, conventionally used in measurements of motion, for source localization purposes? An open-source TurtleBot 3 robot, running Robot Operating System (ROS) on Ubuntu 16.04 LTS, was fitted with a Kromek GR1{sup R} Cadmium Zinc Telluride (CZT) solid-state gamma-ray detector. As a part of ROS, the packages OpenSlam, gmapping, and amcl were used to perform Simultaneous Localization and Mapping (SLAM), determining the robot's position and mapping the surrounding area. Data was acquired via Lidar mounted on top the TurtleBot 3. Detector Calibration Fit: The equation was fit to 365 counts of various energies, distances, and angles. A MATLAB{sup R} program was written to simulate measurements taken a robot on a random walk, with count data and positions discretized into finite element pixels. Using this program, a sample of 100 runs was performed on a map with a simulated source at the center, with a total of 200 of 2 pixels each. Similarly, multiple runs of the filter were performed on recorded robot measurement data. In both simulation and real tests, when corrected for errors (particles placed outside of bounds or on the robot, and simulation-specific errors), corresponding t-tests of predicted x and y-coordinates were within a 95% confidence interval of the actual position. For the real trial, these positions are slightly skewed right in the x-axis as the robot remained mainly to the left side of the source within the sample area. These simulations demonstrate potential validity for the usage of a particle filter as method of radioactive source localization. In the future, true real-time implementation and data fusion may further augment the performance of the robot to localize lost sources. Additionally, identification of multiple sources, determination of source types, and usage of a collimator are areas to potentially be explored.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2017

Modular Platforms for Advanced Inspection, Locomotion, and Manipulation - 17150

Robots can provide remote access, manipulation, and inspection capabilities to augment human workers and improve safety in potentially dangerous decommissioning, radioactive waste management, and emergency response operations. However, such activities may require navigating challenging and unstructured environments, such as those with uneven terrain, obstacles, or loose debris. This remains a difficult task, even for modern robots. What's more, a robot's physical design can inhibit it from accessing hard-to-reach areas such as the tight spaces around, underneath, or inside piping and equipment. To address these challenges, we have developed a series of physically robust hardware modules that can be configured into a variety of robot morphologies, specialized to support different operational needs. Each hardware module consists of a number of onboard sensors and a high performance actuator with a series elastic element to sense and control interaction forces for improved locomotion and manipulation. Using this hardware, we have designed several robotic platforms that support the access, manipulation, and inspection requirements of decommissioning and radioactive waste management. To highlight current capabilities and potential opportunities for technological improvement, we present the outcomes from field demonstrations of our modular platforms at the Office of Environmental Management's Science of Safety Portsmouth Gaseous Diffusion Plant Robotics Challenge. Specifically, results include a serpentine robot climbing vertical structures such as pipes, posts, and supports to demonstrate advanced inspection. Additionally, we discuss field trials of a similar modular configuration that yields a highly dexterous manipulator arm and camera system capable of adding manipulation and inspection functionality to existing structures. Results are presented from inspection tasks in which the manipulator is installed on another mobile robotic platform. Finally, we show our hardware modules can be reconfigured into platforms capable of withstanding significant impacts and of alternative means of locomotion, as may be required to cross terrain too challenging for traditional wheeled robots. Results describe the performance of a hexapod robot that uses proprioceptive feedback to locomote in outdoor trials reminiscent of emergency response conditions. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

Autonomous Coupler Alignment Using Position-Based Visual Servoing in a ROS 2 Framework

As robotic arms are becoming increasingly common alongside humans as collaborative robots, their high precision in motion enables tasks to be performed at significantly higher speeds with reduced disruption in the environment. The Fermi National Accelerator Laboratory is exploring this application by incorporating a UR16e from Universal Robots in a cleanroom setting during assembly of couplers to superconducting radio frequency cavities as part of the PIP-II project. The goal of the robotic assembly process is to precisely position the UR16e robot so that the coupler flange, mounted on the robot’s end-effector, is accurately aligned with and pressed against the cavity flange, requiring only final fastening by a lab technician. This thesis builds upon an initial system in which the robotic process was limited to the alignment phase using position-based visual servoing with an eye-in-hand camera to only align the coupler to the cavity with an offset distance. The objective of this thesis is to further advance autonomous robotic assembly by extending the process. To this end, the entire software framework was reconstructed, as the previous development environment posed significant challenges in modifying the software and adapting to hardware changes. The main contributions of this thesis are as follows: (i) a modular and scalable software framework based on ROS~2 was developed to facilitate performance expansion and interchangeability of software and hardware components; (ii) the desired alignment position for position-based visual servoing was parameterized to enable flexible configuration; and (iii) a methodology was developed to close the offset distance between the coupler and cavity utilizing the internal force-torque sensing capability of the UR16e, as visual feedback is not available during the offset-closing phase. The proposed autonomous robotic assembly reduces assembly time and technician involvement, thereby minimizing the risk of airborne particulate contamination, which is essential in the cleanroom setting. Moreover, the ROS~2-based framework provides a foundation for further expansion and continued advancement of robotic automation in Fermilab.

Giffen, Nickolas [Northern Illinois U.]↗
DOE OSTI2020

Performance Evaluation of Augmented Teleoperation of Contact Manipulation Tasks

At Argonne National Laboratory, an enhanced telerobotic concept has been suggested by providing augmented virtual fixtures for precise and dexterous manipulation. The proposed technology incorporated a human-robot interface that can assist personnel on the processes of Deactivation and Decommissioning in sites of high radiation. It has been implemented on a dual-arm robot system, known as Baxter, by integrating the Robotic Operating System (ROS) with 3D sensors and visual-haptic operator interface. However, what remained before its practical utilization is the capability for precisely placing the virtual fixtures. To this end, the objectives involved camera calibration, which required hardware fabrication and setup, as well as modification and implementation of ROS. The goal of this Research and Development is to develop an augmented-reality- based operator interface for human-inclusive, intelligent, and autonomous robotic system for the Deactivation and Decommissioning (D and D) of radioactive sites. The objectives are to develop: Collaborative Robot; Multi-modal Mixed-Reality Human-Robot Interface; Intelligent and Autonomous Behaviors. In order to achieve this, Baxter's Head-Kinect camera and Left-Hand camera need to be calibrated to overlap the real environment with the simulated environment. Camera calibration, which is crucial for precisely placing the virtual fixtures, was successful after running the simulations. The real and simulated environments overlapped, permitting the utilization of augmented teleoperation and the dexterous manipulation of Baxter for D and D applications in nuclear sites. Future steps: Performance evaluation of augmented teleoperation of contact manipulation tasks: Multiple-Camera 3D Reconstruction and Automation. Oculus Interface: Augmented reality and machine learning for enhanced telerobotic operation (Augmented Tele-autonomy): Machine-learning techniques for complex and flexible autonomous robotic behaviors. Interactive remote operation of robotic systems. Mesh cutting with simulation and real robot.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

The ReSWARM microgravity flight experiments: Planning, control, and model estimation for on‐orbit close proximity operations

Abstract On‐orbit close proximity operations involve robotic spacecraft maneuvering and making decisions for a growing number of mission scenarios demanding autonomy, including on‐orbit assembly, repair, and astronaut assistance. Of these scenarios, on‐orbit assembly is an enabling technology that will allow large space structures to be built in situ, using smaller building block modules. However, like many of these scenarios, robotic on‐orbit assembly involves several technical hurdles, such as changing system models. For instance, grappled modules moved by a free‐flying “assembler” robot can cause significant changes in the combined system inertia, which have cascading impacts on motion planning and control portions of the autonomy stack. Further, on‐orbit assembly and other scenarios require collision‐avoiding motion planning, particularly when operating in a “construction site” scenario of multiple assembler robots and structures. Multiple key technologies that address these complicating factors for autonomous microgravity close proximity operations are detailed in this work, in particular: (1) application of global long‐horizon planning, accomplished using offline and online sampling‐based planner options that consider the system dynamics; (2) adaptation of the recently proposed RATTLE information‐aware planning framework for on‐orbit reconfiguration model learning; and (3) connection with robust control tools to provide low‐level control robustness using current system knowledge. These approaches were demonstrated for an autonomous on‐orbit assembly use case by the RElative Satellite sWarming and Robotic Maneuvering (ReSWARM) experiments using NASA's Astrobee robots on the International Space Station. Results of the ReSWARM experiments are provided along with significant operational and implementation detail discussing the practicalities of hardware implementation and unique aspects of working with the Astrobee free‐flyer robots in microgravity. ReSWARM provides a base set of planning and control tools for robotic close proximity operations, demonstrates them in microgravity, and outlines some of the important hardware aspects that future autonomous free‐flyers will need to consider.

Robotics↗
DOE OSTI2026

Autonomous Hydrogen Fueling Station

This project “Autonomous Hydrogen Fueling Station” covered the autonomous refueling with both gaseous hydrogen and liquid hydrogen. The part on gaseous hydrogen focused on the development of an autonomous robotic fueling arm that would couple to a fuel cell engine for hydrogen refueling without guidance from the forklift operator and budget period. Research was also covered for the robotic fueling with a commercial vehicle. The second phase of the project created the baseline for an autonomous liquid hydrogen transfer system that would minimize boil off losses by operating at thermodynamically efficient state points. For the development of the robotic fueling arm, testing was conducted to establish a baseline measurement of the accuracy and repeatability of a human operator positioning a lift truck in front of a dispenser. The goal was to establish the range of motion required for an autonomous fueling mechanism to mate a hydrogen nozzle with a receptacle on a fuel cell system installed in a forklift. The final design comprised a selective compliance articulated robot arm (SCARA)-type mechanism with two arms for horizontal motion and a ball screw for vertical movement and color and LIDAR cameras were used for marker identification and proximity awareness to guide the robotic arm to its target receptacle. Initial tests resulted in 199 out of 200 successful attempts at autonomous coupling of the dispensing coupler and a fuel cell engine, without hydrogen. The dispenser prototype was modified to include tubing for both hydrogen fuel and air purge lines, but subsequent tests were confounded by the shoulder motor over current errors which limited the robot from getting to the fully inserted position to achieve a positive latch. Robotic hydrogen refueling was successfully demonstrated over 1.5 hours of testing, Plug completed 29 successful latches with an average number of 4 sequential latches before failure. However, a robot capable of placing the nozzle with more force is required for higher reliability. For budget period two, a small scale (10 kg / transfer) automated control system was designed that would operate valves to control pressure and flow of liquid nitrogen between a source and receiving tank with an aim to minimize boil off losses by operating at the most thermodynamically efficient state points. Control system logic flow and a P&ID were developed prior to system safety characterization via HAZOP. A control narrative and system state points were defined. Delays in approval for a change of project objective and procurement issues precluded the construction and test of the final prototype system.

08 HYDROGEN↗
DOE OSTI2017

The Future of Robotics/Remote Handling Solutions for the Nuclear Industry - 17347

The nuclear industry is seeing a resurgence of development and utilization of advanced integrated systems; fused sensor arrays; autonomous, remote and hybrid operations; and augmented reality display and control system interfaces. A new age of 'robotics' and remote handling technologies. For many years the use of robotics in nuclear applications has been done sparingly due to technical limitations, perceived and real reliability issues, perceived and real risk concerns, and cost. Although robotics have been used successfully on a variety of projects globally, the underuse of this technology, particularly within the nuclear industry both public and private, is overwhelming. As the number of complex, high hazard projects in the nuclear industry increases, the use of robotics for maintenance, inspection, repair, decommissioning, and remediation activities will become increasingly vital in the future. The risks associated with direct human exposure are high and thus eliminating the risk, or managing it to acceptable levels by using robotics/remote handling as well as other technologies is critical to success as more extreme environment operations and tasks are undertaken. Recent and ongoing advances in technology now allows us to safely and effectively remove the direct / in-situ human element from these type of activities. All the while delivering the same or better outcomes when considering the alternatives when limited or no direct / in-situ human intervention would be allowed. The biggest obstacles the nuclear industry faces center on the cost, reliability, maintainability, effectiveness and appropriate uses of robotics/remote handling solutions in a nuclear (radiation and/or contamination) environment. In order to mitigate these concerns, a sound approach to the use of robotics needs to be addressed. This approach must include: 1. A better understanding of what technology is available and how it can be utilized across multiple sectors, e.g. Commercial Off-the-Shelf (COTS) technology modified / adapted for the nuclear sector; 2. How to implement technology in an integrated pragmatic approach that is cost effective by combining technological know-how / subject matter expertise (SME) with the equivalent subject matter expertise in regulatory, operational and maintenance requirements and limitations, such that a more complete set of functional and operational requirements can be jointly developed in the process. 3. The integration of requirements (project, site, regulatory, etc.), risk management (human factors) and technology, i.e. a marriage between political, programmatic, and technological factors. As the development of robotic/remote handling technology progresses and the successful implementation on projects is demonstrated, the better off the industry will be. This paper provides an overview of the fundamental issues facing the nuclear industry with regard to effective and successful technology selection, maturation, deployment, and integrated risk management, and offers suggestions on how we may overcome these persistent issues now and in the future. Robotic systems and solution experts that are focused on the integration of proven technologies - and that are an integrated part of the project team from its onset - are a necessity for successful planning during nuclear operations. The approach to nuclear operations should always be, 'what is the simplest, most effective way we can approach a particular project need?'. Understanding and implementing the right technologies is where the true value will be recognized. The integration of systems, which includes more than just robotics, is key when developing schemes for these types of complex operations. Often times during planning, the remote handling needs of the job are set aside to be evaluated at a later time due to risk concerns and lack of knowledge. The issue is, experts in the area of robotics or remote handling are rarely involved in the upfront planning. As a result, unnecessary constraints, risks, and obstacles are imposed on project teams to deliver. If done intelligently, this should be introduced at the forefront of planning. Using this type of sound approach leads to effective task organization for the end user. By developing an overall philosophy that leverages proven technologies with implementation expertise; i.e. solutions versus products, is a recipe for success. This is the area that is under-appreciated in the industry and one that needs to be recognized on a much broader scale. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Automated Inspection of Criticality Control Overpacks for Surplus Plutonium Disposition: Qualification Update – 25313

In an effort to reduce the amount of nuclear waste in South Carolina, the Department of Energy (DOE) tasked the Savannah River Site (SRS) with diluting and disposing of the amount of plutonium in the state. This process involves the movement and shipment of over 100,000 criticality control overpacks (CCOs) throughout the project lifespan, lending itself to the use of automation to reduce worker radiation exposure and more efficiently utilize human capital. Due to the large scope, this overarching process was broken down into several different “automation projects” to be developed. The first opportunity pursued was the receipt and inspection of empty CCO drums coming into SRS, identified as Automation Project 1 (AP1), and is the focus of this paper. AP1 was developed to unpack incoming CCOs and inspect them for unwanted foreign objects and any damage to the drum or its contents. This process is accomplished by the combination of an automated guided vehicle (AGV) that delivers CCOs to a robotic arm which uses a suite of custom tools to disassemble a CCO, inspect the inside and outside of the CCO and its inner criticality control container (CCC), reassemble the CCC and CCO, and apply a tamper indicating device (TID) to the inspected drum. In past years, the robotic work cell had been developed in a small-scale testing facility for proof-of-concept. This year, major improvements were made to the robotic work cell to perform the process, including integration into the final facility where CCOs will be inspected. Other technical improvements include the implementation of sensor feedback and safety relays into the control system to allow the state of the work cell to be better tracked, and additional development of the TID application process to complete the robotic inspection. Further enhancements were made to the robotic vision processes and robot pathing, as well as development on a computer vision inspection process to detect inspection criteria anomalies in CCOs. In addition to developmental improvements, the work cell underwent a six-month testing period to ensure the project requirements were met. Results of this testing period demonstrate the work cell’s capability to meet project throughput goals at an acceptable level, successfully document the status of each CCO inspected, and reduce the toll on technical operations’ human power by two thirds. At the time of this paper, the work cell is capable of autonomously handling up to eight CCOs with an AGV, delivering CCOs to and from the robot work cell, and having a robotic arm perform a full receipt and inspection procedure on each CCO. Moving forward, repeatability will be improved so that these CCOs can be run back-to-back seamlessly, as well as improving the system to handle more significant edge cases and failure modes.

Spivey, Nicholas↗