Scaling Orbital Dynamics to the Laboratory: An Industrial Robot Hardware-in-the-Loop Testbed for Small Satellites
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Engineering - Space vehicles and technology↗
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Results for “robotic hardware”
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Exploring Benchmarks for Self-Driving Labs using Color Matching
Self Driving Labs (SDLs) that combine automation of experimental procedures with autonomous decision making are gaining popularity as a means of increasing the throughput of scientific workflows. The task of identifying quantities of supplied colored pigments that match a target color, the color matching problem, provides a simple and flexible SDL test case, as it requires experiment proposal, sample creation, and sample analysis, three common components in autonomous discovery applications. We present a robotic solution to the color matching problem that allows for fully autonomous execution of a color matching protocol. Our solution leverages the WEI science factory platform to enable portability across different robotic hardware, the use of alternative optimization methods for continuous refinement, and automated publication of results for experiment tracking and post-hoc analysis.
Artificial intelligence↗
Model-Based Ultrasonic Signal Processing for the Nondestructive Evaluation of Additive Manufacturing Components
Ultrasonic testing (UT) for nondestructive evaluation (NDE) is a critical entity necessary to resolve both the quality and precision questions of complex parts evolving from the innovative additive manufacturing (AM) process. This modality provides the essential quantitative information for acceptance and potential flaw detectionof the part under investigation. A primary ingredient in UT besides the required precision robotic hardware for theacquisition of high quality measurement data is the underlying signal processing. It is here that much of the system performance capability resides. In this report,we discuss the basic steps in UT signal processing along with current and future capabilities that must be achieved in order to satisfy the critical demands created by the AM process.
42 ENGINEERING↗
Time-of-Flight Estimation for Nondestructive Evaluation
Ultrasonic testing (UT) for nondestructive evaluation (NDE) is a critical entity necessary to resolve both the quality and precision questions of complex parts evolving from the classical approaches to the innovative additive manufacturing (AM) process. This modality provides the essential quantitative information for acceptance and potential flaw detectionof apart under investigation. A primary ingredient in UT besides the required precision robotic hardware for theacquisition of high-qualitymeasurement data is the underlying signal processing. It is here that much of the system performance capability resides. In this report,we discuss the basic steps in UT signal processing along with current capabilities that must be achieved in order to satisfy the criticaldemands of the various LLNL programs.In itsbasic foundations, signal processing is essentially the “extraction of critical information (signals) from noisy, uncertain data.” Clearly, in a perfect world the best signal processing is none---just make a reliable, noise-free, uncertainty-free, measurement. Unfortunately, even the best of systems is still straddled within the confines and limitations of physical instrumentation. With this in mind, we discuss the development of signal processing techniques toextract the desired UT information from noisy measurement data. We start with a discussion of a simple homogeneous representation of a “part” under investigation and its insonification by an ultrasonicexcitation from a physics-based perspective. Once developed, we briefly discussthe various choices of excitation signals and their tradeoffs.Next,we discuss a simulation approach employing simple models from the signal processing perspective and then move on to the development of the basic signal processing approach to ultrasonic signal processing all based on estimating the pulse arrival estimation. Starting with simple peak detection techniques, progressing to the processing workhorse so-called “matched-filter” and finally to the more sophisticated “model-based matched filter.”The underlying pre-and post-processing of noisy measurement data along with the application of these techniques are subsequently demonstrated on experimental ultrasonic data.Finally, we present some results for processing “weld” data when the ultrasonic excitation signal is not directly available.
42 ENGINEERING↗
Mantisa
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.
Dellana, Ryan↗
Online task-space motion control for positioner-coordinated multi-robot manufacturing systems
Incorporating multiple robotic manipulators into large-scale manufacturing systems enhances production efficiency and expands manufacturing capabilities beyond those of single-robot systems. Workpiece positioners in robotic manufacturing have demonstrated significant benefits for process optimization, but coordination strategies for multi-robot systems with shared positioners have received limited attention. This work presents a task-space coordinated trajectory-tracking control framework for multi-robot manufacturing systems, in which robots coordinate their motions within a shared, dynamic workpiece positioning frame. A workpiece positioner actively adjusts the pose of the manufactured component to enable greater operational concurrency and improve overall production efficiency. The proposed motion-coordination scheme employs a distributed and scalable architecture, supporting coordination across heterogeneous multi-robot systems. Two optimization methodologies are introduced to manage kinematic redundancies and maintain continuous, near-optimal operation throughout the manufacturing process. The first strategy exploits a task-space dimensionality reduction to achieve locally optimal configurations by leveraging symmetry-axis rotations of the tool. The second strategy utilizes the workpiece positioner to drive the coordinated robots toward stable and kinematically favorable configurations. For both optimization strategies, multiple objectives are defined to improve key performance metrics, including manipulability, configuration consistency, proximity to mechanical limits, and motion efficiency. Addressing a key limitation of existing coordination approaches, the framework is designed around online setpoint modification, allowing coordinated robots to respond effectively to in-situ process feedback. The proposed control framework is validated using the Robot Operating System (ROS) middleware on a combination of physical and simulated multi-robot system hardware.
Arbogast, Alex [ORNL] (ORCID:0000000154740723)↗
Robotics for Energy Infrastructure Construction on Earth and Beyond: Pilot Study Exploring Level 3-4 Semi-Autonomous Installation of a Reduced-Scale Photovoltaic Power Plant Prototype: Preprint
There is a growing need to build energy infrastructure at massive scale on both Earth and in space. On Earth, increasing electricity demand from applications such as AI data centers is driving rapid expansion of power systems, while in space, long-duration missions such as lunar operations require reliable and resilient energy infrastructure that can be deployed quickly. These needs outpace the capabilities of conventional construction methods. Robotic construction offers a path to faster, lower-cost, and more consistent deployment, yet most existing approaches focus on automating individual tasks rather than end-to-end assembly. The Industrialized Construction Innovation (ICI) team at the National Laboratory of the Rockies (NLR), in collaboration with the Colorado School of Mines, has been investigating robotics and automation strategies for rapid end-to-end energy infrastructure construction. This paper presents a pilot study demonstrating level 3-4 semi-autonomous, end-to-end robotic assembly of a reduced-scale photovoltaic power plant prototype under terrestrial conditions. The approach combines hardware redesign of photovoltaic components for robotic compatibility, discrete-event and physics-based robotic simulations in synthetic environments, and sim-to-real deployment to execute end-to-end robotic assembly of[NM1.1][NM1.2] tracking components, structural members, photovoltaic modules, and embedded electrical connections. The pilot identifies key limitations like tolerance management, perception and localization, end effector capability, fastening methods, and multi-physics simulation fidelity, that must be addressed to enable end-to-end robotic assembly of full-scale energy infrastructure. The study highlights how these insights inform scaling strategies for terrestrial energy infrastructure and adaptation to unstructured and extreme environments, including off-world scenarios such as robotic assembly of vertical tall lunar towers.
14 SOLAR ENERGY↗
Robotics for Systems Integration in Buildings - Pilot Study of Viable Approaches to Install Hygrothermal and Rigid Electrical Systems: Preprint
The Industrialized Construction Innovation (ICI) team at the National Renewable Energy Laboratory (NREL) has been exploring the use of robotics to integrate hygrothermal, mechanical, electrical, and plumbing systems in prefabricated building assemblies (offsite construction) and 3D Printed buildings (onsite construction). Such multi-system integration tasks often require specialized robots and custom end-effectors for handling a range of rigid and non-rigid building components. This paper begins with a brief overview of the current state of robotics in construction, followed by a pilot study exploring the use of robotics to integrate a simple prototype multi-trade wall assembly composed of structural studs, hygrothermal layer, wall finishing, and electrical fixtures. The study was funded by the Department of Energy's (DOE) Advanced Materials and Manufacturing Technologies Office (AMMTO). Insights about the implementation of design for manufacturing and assembly (DfMA) principles in designing the prototype wall for robotic assembly, and selection of appropriate robotic end effector hardware for handling these components are included. Detailed comparison of computational toolpath simulations of the robotic assembly process and real-life demonstration of the same is presented. Finally, limitations and lessons learned from this study along with future research recommendations for robotic assembly of more complex multi-trade assemblies, including potential scenarios such as robotic outfitting of facilities in extra-terrestrial environments is included.
advanced manufacturing↗
Argonaut - A Robotic System for Cryogenic Environments
Fermilab and the HEP community invest significant resources into liquid argon detectors. The largest and most expensive of these detectors will be located in the Deep Underground Neutrino Experiment (DUNE). However, recent experiences have shown that there are limited avenues of monitoring, intervention, and interaction in the internal liquid environment. This proposal shows a technological path that could provide a valuable tool to ensure or at least improve the management of these HEP detectors. The development of a robotic system named Argonaut will demonstrate several technologies including 1) demonstration of suitable mobility of a small robotic device at liquid argon temperatures, 2) demonstration of wireless communication, 3) demonstration of improved diagnostics capabilities - such as tunable optics with motion control, 4) demonstration of interconnectivity of a robotic system with hardware residing within the detector. This initial research will be a seed for extended development in cold robotics and associated technologies. This work will allow FNAL to contribute a significant technology capability to recent efforts to cryogenic detector operations.
43 PARTICLE ACCELERATORS↗
Robot Mission Planning & Operations (MPO) Software and Hardware System Investigation & Demonstration for Security Applications at Advanced and Small Nuclear Reactors (A/SNRs) Final Report
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21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
TORONE: Total Characterisation by Remote Observation of Nuclear Environments - 20591
This paper describes the autonomous robotic systems developed in the TORONE project (Total Characterisation by Remote Observation of Nuclear Environments) for combined characterisation by remote techniques in nuclear environments. There are four main components to the system. Firstly, robot operation which uses a Robot Operating System (ROS) allowing ease of communication between hardware and software alongside robot vision systems such as Lidar and/or photogrammetry. Secondly, radiation detection instrumentation for gamma and neutron sources which is also collimated for spatial resolution. Thirdly, photonic characterisation instrumentation for remote material identification by means of Raman spectroscopy and Laser induced breakdown spectroscopy (LIBS). Finally, a data management system is described which contains the TORONE characterisation data with the ability to overlay material characterisation information onto 3D maps of the nuclear environment. Preliminary results are described alongside discussion of some of the synergies of the combined approach. There are many applications of such an autonomous system in nuclear decommissioning, waste management and asset management. (authors)
12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
Robotic Mapping and Monitoring of Nuclear Infrastructure
Routine inspection of nuclear infrastructure is currently expensive and slow. To remedy this the Applied Research Center (ARC) at Florida International University (FIU) is developing a field robot capable of gathering valuable data quickly, safely, and cheaply. Motivation: Nuclear infrastructure should be inspected routinely to ensure early detection of problems. This process is expensive, hazardous, and slow. Objective: Develop a platform capable of surveying nuclear infrastructure autonomously. Discussion: The quality of the captured data depends on the success of every component of the robot. Good sensors, hardware, localization, data collection, and autonomy are required. Conclusion: This is a promising approach for surveying nuclear infrastructure. The captured data is rich with information and can be evaluated by both people and algorithms.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
Robotics for Systems Integration in Buildings: Pilot Study of Viable Approaches to Install Hygrothermal and Rigid Electrical Systems
The Industrialized Construction Innovation (ICI) team at the National Renewable Energy Laboratory (NREL) has been exploring the use of robotics to integrate hygrothermal, mechanical, electrical, and plumbing systems in prefabricated building assemblies (off-site construction) and 3D-printed buildings (on-site construction). Such multisystem integration tasks often require specialized robots and custom end effectors to handle a range of rigid and nonrigid building components. This paper begins with a brief overview of the current state of robotics in construction, followed by a pilot study exploring the use of robotics to integrate a simple prototype multitrade wall assembly composed of structural studs, hygrothermal layer, wall finishing, and electrical fixtures. The study was funded by the US Department of Energy's (DOE's) Advanced Materials and Manufacturing Technologies Office (AMMTO). Insights about the implementation of design for manufacturing and assembly (DfMA) principles in designing the prototype wall for robotic assembly, and selection of appropriate robotic end-effector hardware to handle these components are included. Detailed comparison of computational toolpath simulations of the robotic assembly process and real-life demonstration of the same are presented. Finally, limitations and lessons learned from this study are included, along with future research recommendations for robotic assembly of more complex multitrade assemblies, including potential scenarios such as robotic outfitting of facilities in extraterrestrial environments.
advanced manufacturing↗
Robotics for HVAC applications: A critical review and future perspectives
Recent advances in artificial intelligence (AI), enhanced computational capabilities, and innovations in sensors and hardware have driven the increasing development and application of robots in heating, ventilation, and air conditioning (HVAC) systems. We selected and reviewed 101 studies published between 2005 and 2025, sourced from IEEE Xplore, Scopus, Web of Science, and the ACM Digital Library. To analyze these works, we developed a five-dimensional analytical framework (morphology, sensing, navigation, task execution, and system integration), inspired by the Springer Handbook of Robotics and tailored specifically for robotic applications in HVAC. Based on the reviewed studies, six distinct tasks spanning the entire HVAC lifecycle have been identified. Among the six tasks, inspection and maintenance dominate (59 %), followed by indoor monitoring and auditing (21 %), whereas leakage detection, comfort support, and installation/retrofit remain less explored. To address the identified gaps, this review proposes future research directions including investigating robot-aware HVAC design principles, developing multimodal HVAC sensing and data fusion techniques, enhancing robot training and hardware capabilities, and expanding robotic applications beyond Maintenance and Operations (M&O). The findings from this review inform future robotics research for HVAC applications and ultimately enhance system affordability, energy efficiency, resilience or reliability, and occupant environmental comfort. Moreover, it seeks to inspire researchers to explore the intersections of robotics, computer science, building science, and HVAC engineering fostering advancements in this multidisciplinary field.
AI↗
Automated Strain Construction for Biosynthetic Pathway Screening in Yeast
Automation accelerates the Design-Build-Test-Learn (DBTL) cycle for synthetic biology; however, most strain construction pipelines lack robotic integration. Here, in this study, we present the workflow design and source code for a modular, integrated protocol that automates the Build step in Saccharomyces cerevisiae. We programmed the Hamilton Microlab VANTAGE to integrate off-deck hardware via its central robotic arm, enabling automated steps that increased throughput to 2,000 transformations per week. We developed a user interface with the Hamilton VENUS software to support on-demand parameter customization. As a proof of concept, we screened a gene library in an engineered yeast strain producing verazine, a key intermediate in the biosynthesis of steroidal alkaloids. Our pipeline rapidly identified pathway bottlenecks and genes that enhanced verazine production by 2.0- to 5-fold. This technical note provides resources for synthetic biologists designing yeast workflows for biofoundries to screen libraries for pathway discovery/optimization, combinatorial biosynthesis, and protein engineering.
automation↗
Design and Closed‐Loop Motion Planning of an Untethered Swimming Soft Robot Using 2D Discrete Elastic Rods Simulations
Despite tremendous progress in the development of untethered soft robots in recent years, existing systems lack the mobility, model‐based control, and motion planning capabilities of their piecewise rigid counterparts. As in conventional robotic systems, the development of versatile locomotion of soft robots is aided by the integration of hardware design and control with modeling tools that account for their unique mechanics and environmental interactions. Here, a framework for physics‐based modeling, motion planning, and control of a fully untethered swimming soft robot is introduced. This framework enables offline co‐design in the simulation of robot parameters and gaits to produce effective open‐loop behaviors and enables closed‐loop planning over motion primitives for feedback control of a frog‐inspired soft robot testbed. This pipeline uses a discrete elastic rods (DERs) physics engine that discretizes the soft robot as many stretchable and bendable rods. On hardware, an untethered aquatic soft robot that performs frog‐like rowing behaviors is engineered. Hardware validation verifies that the simulation has sufficient accuracy to find the best candidates for sets of parameters offline. The simulator is then used to generate a trajectory library of the robot's motion in simulation that is used in real‐time closed‐loop path following experiments on hardware.
Huang, Xiaonan↗
Commercial-Off-The-Shelf (COTS) Hardware Implementation Method for Real-Time Control of Mobile Robotics and UAVs
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Coletti, Christian↗
Development of NDE/NDT Tools for High-Volume & High-Speed Inspection of CFRP Structures in Automotive Manufacturing
Main advantages of the air-coupled ultrasound testing (ACUT) and electromagnetic testing (EMT) techniques for NDE of CFRP composites were non-contact sensing, scalability for high-speed inspection, cost-effectiveness, and non-hazardous operation. Despite these advantages, no systems that would satisfy the project requirements were commercially available. Hence, one of the major efforts of the Michigan State University (MSU) team at the initial stage of the project was to close this technological gap by developing, optimizing, and validating array sensors that would provide sufficient sensitivity, spatial coverage, and resolution for robust defect detection. Optimization of the ACUT and EMT sensor designs was performed using experimentally validated finite element models. Initial experiments using array probes were conducted on relatively flat CFRP samples. In parallel, the MSU team designed and assembled a portable platform with two robotic arms. The robots were equipped with newly designed sensors that enabled high-speed NDE of curved CFRP parts. Presently, the developed robotic platform can be used as a demo/template NDE system, which is easily adaptable to manufacturing environments and in-line NDE. The ACUT NDE system developed by the MSU team used a high-power 4-channel pulser receiver for parallel data acquisition. The array probes were designed by stacking commercially available ACUT transducers, which operated in the frequency range between 100 kHz and 500 kHz. MSU optimized the excitation procedure and developed wave focusing cones so as to reduce the crosstalk between the transducers and to provide higher pulse repletion frequency (PRF). The through-transmission (TT) and single-side access (SSA) inspection modes were successfully implemented. In the TT-ACUT, structural defects in CFRP were detected by passing ultrasonic waves through the test part. Hence, the ACUT transmitters and receivers needed to be placed on the opposite sides of the test part. In the SSA-ACUT, guided waves (GW) were excited in the test part using the transmitters and were sensed by the receivers from the same side. Multi-channel TT-ACUT and SSA-ACUT provided high-speed NDE, and were successfully validated on CFRP test samples with interlaminar delaminations and other embedded defects The EM techniques developed by the MSU team included: 1) eddy current testing (ECT), 2) capacitive imaging (CI) and hybrid dual-mode imaging. In ECT, structural damage was detected in CFRP using coils sensor arrays. In ECT, the excitation magnetic field is generated by passing an alternating current through a coil, which is placed above the test sample. The excitation field penetrates the conductive sample and induces the eddy currents in its transect. In turn, the eddy currents generate the reaction field, which affects the total field sensed by a coil. Hence, the presence of structural flaws will alter the eddy current flow and the picked-up signal. ECT is mostly sensitive to local changes of the electric conductivity of the test sample, and CFRPs are mostly conductive in the direction of carbon fibers. Hence, ECT was well suited for the detection of fiber damage/fiber irregularities. The MSU team developed printed circuit boards (PCB) with coil sensor arrays optimized for NDE of CFRP. Unlike most commercial probes designed for ECT of metallic structures, the MSU array probes were designed for operation in [1-10] MHz frequency range, which was optimal for low-conductive CFRP. Multiple sensing topologies (coil groups excitation/sensing arrangements) were implemented and successfully validated. Capacitive Imaging (CI) technique developed by MSU was complementary to ECT. In contrast to ECT, which was sensitive to local changes of the electrical conductivity, the CI was sensitive to local changes of the dielectric constant. Therefore, CI could provide information about matrix damage/matrix irregularities in CFRP. The MSU CI sensor arrays were made of multiple circular or rectangular open-plate capacitors printed on PCB. Sensors of this type are not commercially available. In addition to ECT and CI, the MSU team developed a hybrid (dual-mode) inductive/capacitive measurement technique that synergistically combined the benefits of inductive and capacitive sensing for rapid NDE of fiber reinforced polymer (FRP) composite structures. Fiber damage and fiber irregularities in FRPs were detected by configuring hybrid sensors as coil sensors. Similarly, matrix damage, matrix irregularities and interlaminar delaminations were detected by configuring hybrid sensors as capacitive sensors. ECT and CI were performed sequentially by means of electronic switching. Hence, eliminating the need for mounting two separate sensor arrays on the probe. Portable robotic platform was developed by MSU for multi-technique high-speed NDE of CFRP test parts. The platform had two 6-axis robots, which enabled inspection of curved parts in approximately a 6×6×6 ft 3 active scan area. On the software side, the MSU team integrated scripts for NDE hardware control with scripts for robot motion control. MSU also implemented automated path planning for the robots, reconstruction of part’s surfaces via stereovision, 3D rendering of inspection data, and image processing algorithms for enhanced defect detection. Automotive composite parts manufactured by Plasan Composites from Phase I were used to validate the ACUT and EMT techniques on representative testbeds. Among those parts were three X-braces for a Dodge Viper, one composite calibration plaque with known defects at known locations, and four other test sections, including sections from a front splitter, a corner section from a composite hood, and a high-pressure RTM panel made using non crimp fabric. Other test samples included CFRP and GFRP calibration plates with fiber/matrix defects fabricated at MSU/CVRC.
36 MATERIALS SCIENCE↗