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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

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)↗
DOE OSTI2026

An adaptive model-free robotic force control strategy for hydrodynamic real-time hybrid simulation of floating offshore wind turbines

Real-time hybrid simulation (RTHS) - a cyber-physical testing approach - promises to enhance the simulation fidelity of the model-scale experiments used to prototype floating offshore wind turbines (FOWTs). In hydrodynamic RTHS (hydro-RTHS), actuators emulate aerodynamic forces on model-scale FOWT specimens subjected to physical waves in a hydrodynamic laboratory. Robotic arms are promising candidates for actuation in hydro-RTHS due to their compact multi-degree-of-freedom (DOF) capabilities. Unlike classical RTHS for seismic applications, which typically relies on displacement control, hydro-RTHS requires 6-DOF force control on newly designed floating prototypes in a model-scale setting, which presents significant challenges, including modeling uncertainties, directional asymmetry, configuration drift, bandwidth limitations, and time-varying delays. To mitigate these constraints without extensive pre-test calibration, this study proposes an adaptive model-free robotic force control strategy that combines task-space explicit force control with a secondary joint-space pose-keeping task. The Adaptive Feedforward Compensator (AFC) is integrated into the force control loop to compensate for time-varying delay. Experimental testing was conducted using a Franka Emika Panda robotic arm with a 1:50 scale FOWT specimen under operational wind and wave conditions. Results demonstrate stable and consistent 6-DOF force tracking. Effective delay compensation was observed, with low-frequency delay reductions ranging from 71.4% to 91.8% and improvements in low-frequency surge force tracking of 25.0% to 52.1%. This study enhances robotic actuation performance in hydro-RTHS and introduces a force control strategy that supports reliable robotic operation in uncertain floating environments. Future work will explore disturbance-observer mechanisms to further enhance wave rejection capabilities under extreme wind and wave conditions.

17 WIND ENERGY↗
DOE OSTI2024

Herbicide‐resistant weed management with robots: A weed ecological–economic model

The heavy reliance on herbicides for weed control has led to an increase in resistant weeds in the United States. Robotic weed control is emerging as an alternative technology for removing weeds mechanically using artificial intelligence. We develop an integrated weed ecological and economic dynamic (I‐WEED) model to examine the biophysical and economic drivers of adopting robotic weed management and simulate the optimal timing and intensity of robotic adoption within and across growing seasons. We specify a cohort‐based weed growth model that relates yield damages to effective weed density and treats the susceptibility of weeds to herbicides as a renewable resource that can be regenerated by using mechanical weeding robots, due to a fitness cost that makes resistant weeds less prolific. Compared to myopic weed management which ignores resistance development, forward‐looking management leads to earlier adoption of robots and treating robots as complements instead of substitutes to herbicides. This weed management results in adopting fewer robots, deploying robots on a smaller portion of the land, higher profitability, and lower yield loss in the long run, relative to myopic management. Counterintuitively, myopic management leads to a lower resistance level through its higher robot adoption intensity. We also find that a lower level of initial weed seed resistance and/or a higher fitness cost result in a higher level of resistance because they create incentives for farmers to delay the adoption of robotic weed control. Our analysis shows the importance of jointly considering the interactions between weed ecology and economics in analyzing the incentives and effects of robotic weed management on weed resistance.

agricultural robotics↗
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 OSTI2023

Self‐Propelling Macroscale Sheets Powered by Enzyme Pumps

Abstract Nanoscale enzymes anchored to surfaces act as chemical pumps by converting chemical energy released from enzymatic reactions into spontaneous fluid flow that propels entrained nano‐ and microparticles. Enzymatic pumps are biocompatible, highly selective, and display unique substrate specificity. Utilizing these pumps to trigger self‐propelled motion on the macroscale has, however, constituted a significant challenge and thus prevented their adaptation in macroscopic fluidic devices and soft robotics. Using experiments and simulations, we herein show that enzymatic pumps can drive centimeter‐scale polymer sheets along directed linear paths and rotational trajectories. In these studies, the sheets are confined to the air/water interface. With the addition of appropriate substrate, the asymmetric enzymatic coating on the sheets induces chemically driven, buoyancy flows that controllably propel the sheet's motion on the air/water interface. The directionality and speed of the motion can be tailored by changing the pattern of the enzymatic coating, type of enzyme, and nature and concentration of the substrate. This work highlights the utility of biocompatible enzymes for generating motion in macroscale fluidic devices and robotics and indicates their potential utility for in vivo applications.

Song, Jiaqi↗
DOE OSTI2023

Self‐Propelling Macroscale Sheets Powered by Enzyme Pumps

Nanoscale enzymes anchored to surfaces act as chemical pumps by converting chemical energy released from enzymatic reactions into spontaneous fluid flow that propels entrained nano‐ and microparticles. Enzymatic pumps are biocompatible, highly selective, and display unique substrate specificity. Utilizing these pumps to trigger self‐propelled motion on the macroscale has, however, constituted a significant challenge and thus prevented their adaptation in macroscopic fluidic devices and soft robotics. Using experiments and simulations, we herein show that enzymatic pumps can drive centimeter‐scale polymer sheets along directed linear paths and rotational trajectories. In these studies, the sheets are confined to the air/water interface. With the addition of appropriate substrate, the asymmetric enzymatic coating on the sheets induces chemically driven, buoyancy flows that controllably propel the sheet's motion on the air/water interface. The directionality and speed of the motion can be tailored by changing the pattern of the enzymatic coating, type of enzyme, and nature and concentration of the substrate. This work highlights the utility of biocompatible enzymes for generating motion in macroscale fluidic devices and robotics and indicates their potential utility for in vivo applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Umbra (core)

Umbra is a flexible simulation framework for complex systems that can be used by itself for modeling, simulation, and analysis, or to create specific applications. It has been applied to many operations, primarily dealing with robotics and system of system simulations. This version, from 4.8 to 4.8.3b, incorporates bug fixes, refactored code, and new managed C++ wrapper code that can be used to bridge new applications written in C# to the C++ libraries. The new managed C++ wrapper code includes (project/directories) BasicSimulation, CSharpUmbraInterpreter, LogFileView, UmbraAboutBox, UmbraControls, UmbraMonitor and UmbraWrapper.

Bradley, Jon David↗
DOE OSTI2022

Shape-driven, emergent behavior in active particle mixtures

Abstract Active particle systems can vary greatly from one-component systems of spheres to mixtures of particle shapes at different composition ratios. We investigate computationally the combined effect of anisotropy and stoichiometry on the collective behavior of two-dimensional active colloidal mixtures of polygons. We uncover three emergent phenomena not yet reported in active Brownian particle systems. First, we find that mixtures containing hexagons exhibit micro-phase separation with large grains of hexagonal symmetry. We quantify a measurable, implicit ‘steric attraction’ between the active particles as a result of shape anisotropy and activity. This calculation provides further evidence that implicit interactions in active systems, even without explicit attraction, can lead to an effective preferential attraction between particles. Next, we report stable fluid clusters in mixtures containing one triangle or square component. We attribute the fluidization of the dense cluster to the interplay of cluster destabilizing particles, which introduce grain boundaries and slip planes into the system, causing solid-like clusters to break up into fluid clusters. Third, we show that fluid clusters can coexist with solid clusters within a sparse gas of particles in a steady state of three coexisting phases. Our results highlight the potential for a wide variety of behavior to be accessible to active matter systems and establish a route to control active colloidal systems through simple parameter designs.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

2021 Smoky Mountains Conference Data Challenge Synthetic-to-Real Domain Adaptation for Autonomous Driving Dataset

The dataset is comprised of both real and synthetic images from a vehicle's forward-facing camera. Each camera image is accompanied by a corresponding pixel-level semantic segmentation image (all files are .png files). In total, the dataset contains 5600 images in the training/validation set and 1400 images in the testing set. The training dataset contains mostly synthetic RGB images collected with a wide range of weather and lighting conditions using the CARLA simulator [1]. In addition, the training data also includes a small pre-selected subset of data from the Cityscapes training dataset – which is comprised of RGB-segmentation image pairs from driving scenarios in various European cities [2]. The testing data is split into three sets. The first set contains synthetic CARLA images with weather/lighting conditions that were not present in the training set. The second set is a subset of the Cityscapes testing dataset. Finally, the third set is an unknown testing set which will not be revealed to the participants until after the submission deadline. [1] Dosovitskiy, A., Ros, G., Codevilla, F., Lopez, A., and Koltun, V. (2017, October). CARLA: An open urban driving simulator. In Conference on robot learning (pp. 1-16). PMLR. [2] Cordts, M., Omran, M., Ramos, S., Rehfeld, T., Enzweiler, M., Benenson, R., ... and Schiele, B. (2016). The cityscapes dataset for semantic urban scene understanding. In Proceedings of the IEEE conference on computer vision and pattern recognition (pp. 3213-3223).

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Solar Spectrum Conversion for an Algae Bioreactor (CRADA Final Report)

This project focused on developing advanced optical coatings to improve solar energy utilization. The research aimed to create lanthanide-doped upconversion nanoparticles (UCNPs) capable of capturing unused near-infrared (NIR) light from the sun and converting it into visible light (blue and red photons) that can be used for photosynthesis. The primary goal was to identify, synthesize, and integrate highly efficient UCNPs into a transparent thin-film device. Through a comprehensive workflow involving computer simulations, high-throughput robotic synthesis, and detailed optical characterization, the project successfully developed a high-performance material. The key technical achievement was the creation of a core-shell UCNP (NaYF₄:20%Yb³⁺, 2%Er³⁺ coated with a 10 nm NaYF₄ shell) that demonstrated a quantum yield of 3.2% for converting 980 nm NIR light into visible light. Transparent thin films fabricated from these nanoparticles showed excellent optical properties, confirming their potential for practical applications. This research adds to the scientific understanding of energy transfer in lanthanide materials and demonstrates a technically effective method for creating efficient light-converting coatings. The primary benefit to the public lies in the potential for these coatings to enhance the efficiency of solar-driven processes, such as boosting the growth of algae in photobioreactors for biofuel production.

14 SOLAR ENERGY↗
DOE OSTI2020

Advanced Methodology and Preliminary Measurements of Molecular and Mechanical Properties of Heart Valves under Dynamic Strain

Mammalian heart valves are soft tissue assemblies with multi-scale material properties. This is because they are constructs comprising both muscle and non-contractile extracellular matrix proteins (such as collagens and proteoglycans) and transition regions where one form of tissue structure becomes another, significantly different form. The leaflets of the mitral and tricuspid valves are connected to chordae tendinae which, in turn, bind through papillary muscles to the cardiac wall of the ventricle. The transition regions between these tissue subsets are complex and diffuse. Their material composition and mechanical properties have not been previously described with both micro and nanoscopic data recorded simultaneously, as reported here. Annotating the mechanical characteristics of these tissue transitions will be of great value in developing novel implants, improving the state of the surgical simulators and advancing robot-assisted surgery. We present here developments in multi-scale methodology that produce data that can relate mechanical properties to molecular structure using scanning X-ray diffraction. We correlate these data to corresponding tissue level (macro and microscopic) stress and strain, with particular emphasis on the transition regions and present analyses to indicate points of possible failure in these tissues.

valve failure↗
DOE OSTI2017

Automation Toward Tether-less Robotic Operations in Nuclear Facilities - 17474

Automation capabilities that enable communication-denied nuclear robotic operations have come of age. These layer over tethered operation or enable un-tethered systems for some operations. Tele-operated, tethered devices are traditionally preferred for nuclear remote systems. Tethers provide comm, power, and a means for mechanical extraction. They also restrict mobility and create additional failure points, and in some cases, circumstances preclude mechanical recovery by tether. Tethering has superb advantages where it is viable, but a subset of nuclear EM challenges compel mobile remote systems that forgo tethering. Tethering was essential at a time when autonomy or wireless comm could not accomplish viable operations, but now an emerging class of un-tethered exploration and service robots are compelling for situations where tethers compound waste and exposure, or are not viable. Technical advances in localization, modeling, planning, autonomy, integration and reliability have made it possible to augment tethered operations or operate altogether without tether in selective operations. Tether preclusion technologies include localization, perception, navigation, safeguarding and task prescription. These effectively accomplish tasks like way-point following, wall-following, coverage patterning, navigate-to-goal, next-best view and many others. Although these are not yet general for the broad agenda of the nuclear complex, these are already useful for many operations. These provide a foundational base that can be built upon over time for more complex operations yet to come. As a context and analog study, the technologies are exhibited by robotically (without tether) modeling a coal mine with tracks and train cars. This is analogous to technology and operation that might apply for inspection of waste storage at WIPP or the PUREX tunnels. Autonomous exploration of this nature is within state-of-art and possible with or without tether. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Teleoperation of Construction Robots Using Human Interaction: Case Study Examples: Preprint

The integration of advanced teleoperation methods in construction robotics has the potential to enhance productivity and safety in demanding environments. Among different methods, hand gestures have emerged as an intuitive approach, enabling seamless communication between human operators and robotic systems. This study demonstrates the use of hand gestures for controlling a model robotic excavator and a virtual robotic arm in construction applications. Two case study examples are presented. In the first case study, a series of hand gestures are performed to control a model robotic excavator's bucket and arm movements. The second case study focuses on using hand gestures to control a virtual robotic arm to perform a material handling task in a simulated environment. In both cases, the performed hand gestures are all successfully captured and interpreted by the gesture-based teleoperation method to conduct the corresponding tasks, which demonstrates the application of the gesture-based control method for various types of construction robots. Also, the limitations of the gesture-based teleoperation method (e.g., recognition delay, sensitivity to motion outliers) are discussed. Future work will focus on developing a digital twin system to support gesture-based teleoperation for a wider range of construction robots.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2018

Soft Robotic Glove System for Wearable Haptic Teleoperation - 18373

Managing nuclear waste is a difficult, dangerous, and costly task. Teleoperation of robotic operators is an important functionality for this application, allowing robotic devices to operate in dangerous environments while still leveraging the existing abilities and technical knowledge of human workers. One difficulty in implementing effective teleoperation systems is that human operators rely on more senses beside sight: in particular, touch. The sense of touch could provide significant benefits for teleoperation, preventing environmental mishaps that could cost millions of dollars. To help remedy this problem, we present a soft haptic feedback glove system. The primary functionality of this system is to provide tactile and force feedback on the user's hands. This was achieved using custom cylindrical pneumatic actuators. These actuators consist of plastic sheeting folded into a hollow-walled cylinder which is connected to a pressure source. When pressurized, the cylinder walls expand and the cylinder straightens, with the force being related to the pressure. The glove system has one of these actuators over each of the user's three main fingers (index, middle, and thumb), where pressurizing the actuator applies a reaction force to the finger of the user, mimicking the resistance of a grasped object. The expansion of these actuators also causes them to physically press against the user's fingers, giving them the feeling of contact. To demonstrate the usability of this system, we implemented a virtual environment in V-REP simulating the interactions between a robotic Jaco Arm and a floating ball. This simulation receives hand and figure positions from the haptic glove and used them to drive the state of the simulated Jaco Arm. In response to the interactions between the Jaco and the floating ball, the simulation returns commands to the glove, instructing it to pressurize or depressurize its actuators as appropriate, allowing the user to feel the ball in their hand. We tested users in their ability to prevent the ball from floating away using this system with and without the haptic feedback. Results show that the addition of haptic feedback significantly improved the ability of users to interact precisely with the environment. We also used the finger positions of the haptic glove to control a physical robotic hand, and demonstrated the system's usability for control of real robots, though the lack of sensors on the robot made providing the tactile feedback impractical. However, there is more to grasping and holding an object than just the feeling of contact and the resistance to closing one's hand. The weight of the object will apply forces to the user's other joints as they hold it. To this end, we added a haptic feedback device for the user's wrist, a technique that can be generalized to the user's other joints. This is made up of reverse Pneumatic Artificial Muscles (rPAMs) stretching across the wrist between mounts on the hand and forearm. These rPAM actuators are tubes of silicone wrapped in thread such that they extend when pressurized. This extension can apply torque on the user's wrist, mimicking the feeling of gravity, or allowing the simulation of additional contact forces (such as the user's hand impacting an object). We tested this wrist device independently using a simulated path-following experiment. Users showed a significant improvement in performance when aided by haptic feedback during sinusoidal path experiments, demonstrating the usability of this approach. We then integrated the two systems, further demonstrating the usability of this approach. This project represents the first step towards a more effective robotic teleoperation system, allowing skilled human workers to perform tasks more effectively while remaining out of danger. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Sim2Real Autonomous Robotic Exploration [Poster]

Autonomous robots offer promising solutions for exploration in environments that are inaccessible or hazardous to humans. Despite this, physical training of such robots is often constrained by safety risks, high cost or limited accessibility. This project presents an end-to-end simulation to reality pipeline leveraging Nvidia Isaac Sim and Boston Dynamics' Spot to enable autonomous navigation in indoor environments. A reinforcement learning policy is first trained using Nvidia Isaac Lab to establish Spot's locomotion pattern. Virtual LiDAR sensors are then integrated to perform SLAM-based navigation using simulated odometry. Finally, the simulated navigation scheme is transferred to a physical Spot robot to inspect and record images of a real-world room by repeating the learnt trajectory. The proposed framework highlights the potential of scalable training in simulation and reliable deployment in physical environments. Future directions include dynamic trajectory generation in unseen and challenging environments and integration of environmental sensing like temperature, radiation or humidity via sensor and material simulation.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Using Contact to Increase Robot Performance for Glovebox D and D Tasks - 18227

Glovebox decommissioning tasks usually require manipulating relatively heavy objects in a highly constrained environment. Thus, contact with the surroundings becomes inevitable. In order to allow the robot to interact with the environment in a natural way, we present a contact-implicit motion planning framework. This framework enables the system, without the specification in advance of a contact plan, to make and break contacts to maintain stability while performing a manipulation task. In this method, we use linear complementarity constraints to model rigid body contacts and find a locally optimal solution for joint displacements and magnitudes of support forces. Then, joint torques are calculated such that the support forces have the highest priority. We evaluate our framework in a 2.5D, quasi-static simulation in which a humanoid robot with planar arms manipulates a heavy object. Our results suggest that the proposed method provides the robot with the ability to balance itself by generating support forces on the environment while simultaneously performing the manipulation task. (authors)

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

Concrete Inspection in Remote Areas with Robotic Arms

The use of non-destructive examination (NDE) to assess the conditions of concrete structures has received extensive attention in recent years. NDE analysis techniques are used to evaluate the properties of materials and to ensure the integrity of structures without causing damages to them. NDE inspection is often performed manually by certified technicians, however in remote and high hazard environments this is impossible or undesirable for human safety. Development of remote and robotic technologies to perform these essential inspections is of interest to the DOE EM complex due to its aging infrastructure and hazardous environments. This goal of this seedling was to develop techniques to remotely examine inaccessible concrete structures and to evaluate results collected remotely to those obtained by human hand. Additionally, two promising state of the art NDE instruments were identified to be used for the characterization to include the new Proceq Ground Penetrating Radar (GPR) which generates results in 3D using Augmented Reality. A test bed was built to develop and evaluate deployment techniques of the NDE instruments with a robotic arm. Concrete test forms simulating the rough concrete surfaces, strength, composition and potential structural defects that can be found at our DOE EM facilities were built for the examination. Initial NDE instrumentation data collection has been performed on the concrete test forms.

47 OTHER INSTRUMENTATION↗
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↗