A Preliminary Cyber-Physical Security Assessment of the Robot Operating System (ROS)
Abstract Not Provided
Engineering(42)↗
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ROS-Ethereum: A Convenient Tool to Bridge ROS and Blockchain (Ethereum)
Robot Operating System (ROS) has received widespread utilization with the development of robotics, self-driving, etc., recently. Meanwhile, the other technology blockchain is frequently applied to various fields with its trustworthy characteristics and immutability in data storage. However, ROS has no ability to interact with the blockchain, which hinders research in related fields. Therefore, we wonder if we can develop a convenient tool to bridge ROS and blockchain. Inspired by this, we propose ROS-Ethereum. It bridges ROS and Ethereum, a widely used blockchain platform. ROS-Ethereum is based on the User Datagram Protocol (UDP) communication mechanism and the SM algorithm family along with Ethereum technology. Simply put, ROS-Ethereum allows users to invoke the contract when interacting with the blockchain, which makes this process easier and safer. We conduct experiments in real robots to verify the effectiveness of ROS-Ethereum and evaluate it from the following metrics: (1) the encryption efficiency and stability of the algorithm and (2) ROS-Ethereum transaction response time and packet loss rate.
Zhang, Shenhui↗
ROS-DOE: Leveraging Open-Source Robotics Software for the DOE-EM Mission? - 17181
In order to establish a common software framework for its robotic systems, the United States Department of Energy - Environmental Management (DOE-EM) is considering the possibility of extending the Robot Operating System (ROS) open source robotics software to address the varied, complex challenges facing DOE-EM. The effort, preliminarily called ROS-DOE, would enhance the reliability, robustness, security, and user friendliness of ROS to meet the requirements of the nuclear waste remediation mission, and those of DOE as a whole. As envisioned, the ROS DOE program would also support rapid progress to mature cross-cutting capabilities including supervised autonomy, inter-operability with off-the-shelf industrial equipment, and physics-based robot simulation (i.e., Gazebo). This paper provides background context about the current state of ROS software and its supporting community, surveys DOE-EM needs and requirements for robotic solutions, and analyzes the gaps between the current state of ROS and those needed for DOE-EM robotics. It then identifies new capabilities that are recommended for ROS-DOE and outlines software development practices that could be leveraged to blend the best of the open-source world with high-reliability software development practices. (authors)
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Autonomous Radiation Mapping and Quantification using an Unmanned Ground Vehicle. Part I - Environment Mapping
When characterizing facilities, advanced autonomous systems are safe, efficient, and cost-effective tools, which can safely deploy state-of-the-art instrumentation without exposing workers to radiation risks. One main focus of the research is the visual mapping of the environment.This paper presents a framework for the mapping aspect that utilizes lidar and SLAM technologies coupled with a monocular camera to create a point cloud of the environment. Upon completion, the present research work aims to provide an autonomous mobile robot the capability to localize itself and aid the user with visualizing the radiation data. Challenges: C++ node needs to properly synchronize image and point cloud data. 3D lidar has resolution of ± 3 cm. Proper camera calibration needed. Transforms need to be precise for proper alignment of image and point-cloud. Results: Voxelated point clouds. Accurate colors from calibrated cameras including details smaller than lidar resolution. Developed Robotics Operating System (ROS) package for ease of transfer to other robot platforms.
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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)
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Using ROS for Robotic Control [Slides]
The use of robots is important, to help prevent people from being exposed to hazardous materials within a glovebox. The research proposal for the summer was to make a pick and place demo for a seven degrees-of-freedom Motoman Sia5d robot. The Robot Operating System (ROS) was used and the knowledge of C++ and Linux had to be applied. The robot was used to pick up and sort four objects (cylinder, sphere, rectangular prism, and cone) within a virtual environment.
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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)↗
Robotic Non-destructive Test of Concrete Structures with GPR, Impact Echo and 3D Vision - 19540
Structural members come across with various internal defects that cannot be evaluated visually. Instead, hand-held nondestructive sensors are used to detect such defects. In many situations, the hand-held NDT is not possible in high-risk structures because of limited access or safety issues. Therefore, Robotic NDT plays major role in assessing such structures. Robot Operating Systems (ROS) is a powerful open source tool, which is used to program and control robots and other devices enabling one to use sensors, devices and new functionalities such as autonomous navigation, visual perception. For the research presented, ROS is used to program the Sawyer robot arm manufactured by Rethink Robotics. The control system for the robot ensures the ability to adapt to different weights of integrated measuring devices and measured force applied against the wall with a wheeled measuring device while making a remote sweep. Twelve reinforced concrete (RC) beams built with characterized defects are evaluated with the robotic arm integrated with the measuring devices. The RC beams are characterized by voids, corrosion and debonding problems of rebars. The Impact Echo and Ground Penetrating Radar (GPR) devices attached to the robot arm are used to measure the material properties of the concrete beams. The robot arm ensures consistency and uniformity of measurement even in obscure locations. Infrared cameras are used to obtain 3D images of the surfaces of the concrete structures. Roughness is analyzed using computer vision techniques prior to the use of other sensors that are in touch with the surfaces. The computer vision is also used to handle the images collected from GPR sensor. Hand-held NDE is also performed to verify the results obtained by robotic examination. (authors)
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Automated Glovebox Work-cell Design - 18370
Los Alamos National Laboratory (LANL) is the primary plutonium science and manufacturing facility in the United States supporting multiple national security programs. It is responsible for completing a high variety of small-batch manufacturing tasks requiring the handling and precision machining of Special Nuclear Materials (SNM). Given the myriad of tasks that must be completed in a limited workspace, LANL intends to utilize flexible, multi-use robotic work-cells capable of completing a variety of mission critical tasks in a single glovebox with no re-tooling needed between batch jobs. This approach would allow LANL more flexibility in its production schedule and to meet its future production and research objectives. In this paper, we present a system that integrates multiple sensors and other manufacturing peripherals into existing glovebox infrastructure. Currently, a technician can place an object in the work area where vision sensors and supervisory software identify the object and its pose and automatically determine which manufacturing task to complete. Pose uncertainty is addressed in real-time by the task planner, eliminating the need for fixtures. Grasps are validated using pressure sensors, payload sensors, and grasp quality metrics to ensure that objects are not dropped or damaged during manipulation. The robot, sensors, and peripherals are controlled using open-source software built utilizing ROS (Robot Operating System), which minimizes redevelopment and allows for re-use and extensibility. Established capabilities support vision, collision-free path planning, and more, minimizing development time. For this effort, particular attention was given to the integration of general peripheral devices (drill, chuck, etc.), which is critical to efficiently utilizing ROS in manufacturing environments. This integration is achieved with an in-development framework that allows for quick integration of peripherals, including I/O devices and motors. Contact tasks utilize the Generalized Contact Control Framework (GCCF) previously developed at UT Austin. GCCF allows application developers to easily define multiple contact control tasks for a single robot. This paper summarizes the key software components necessary to develop the multi-use work-cell including existing ROS components. UT-developed software for grasp validation, peripheral integration, and contact control is presented in more depth. Finally the glovebox system is demonstrated completing a set of tasks with no fixturing necessary. Primary tasks include surface preparation/ablation, drilling, press-fitting, and sorting, as well as supporting material transfer and inspection tasks. The glovebox work-cell reduces cost, operator dose, ergonomic issues, and time loss due to material transfer between gloveboxes that only support one task. If multiple glovebox work-cells are in use, they have the potential to eliminate bottlenecks and scale production capabilities beyond current limits. (authors)
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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.
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R and DE Robotic Sensor Intern Team: Remote 3D Mapping Overview
The Department of Energy (DOE) nuclear complex includes many hazardous and challenging environments that must be inspected remotely and routinely for structural integrity evaluation and long-term planning purposes. The H-Canyon Air Exhaust (HCAEX) Tunnel biannual inspection is an example of such an environment. Presently inspections are performed by teleoperated robotic crawlers provide low resolution video feedback to the structural engineers. Advanced sensors such as Lidar and panospheric hi-res cameras have the potential to provide additional valuable data in future inspections. UT-Austin Lidar work in support of an H-Canyon deployment began with the DOE EM sponsored H-Canyon Integrated Research Project. The R and DE Robotic Sensor intern team includes two of the UT-Austin Masters students working on Lidar development to facilitate the pulling of university developed solutions to the field. The goal of this project is to develop a suite of sensors that could be used to gather advanced data in future HCAEX tunnel inspections. Of particular interest is the ability to map the tunnel walls at an accuracy that will allow for the comparison of two scans performed at different time periods to estimate the concrete erosion rate. Additionally, the development of the 3D point cloud in the GPS denied environment is the first step in being able to collect and overlay other 3D data such as radiation mapping. Project specific goals include: - Design and develop 3D mapping sensor suite. Merge Lidar point cloud with high res camera images Incorporate Inertial Measurement Unit (IMU) to assist with positioning. - Develop sensor software and user GUI Sensor data collection and integration software User GUI for reach back system. - Test solution on crawler in tunnel test bed Use crawler base similar to H-Canyon planned crawler Design and build test bed simulating tunnel conditions. To facilitate rapid sensor integration, software coding and user GUI development, the Robot Operating System (ROS) was employed as the development platform. ROS is a set of open source software libraries and tools that assist with the building of robot applications. ROS includes drivers for many sensors, state-of-the-art algorithms, and powerful developer tools. Sensors selected for the summer intern solution included assessment as to whether they possessed ROS drivers and associated sample code. Additionally, the ROS 3D Robot Visualizer (rviz) tool has been employed.
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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.
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300_underground robot (final research report)
Recent advancements in mobile robotics have displayed impressive capabilities in traversing and accessing areas that are inaccessible to humans either due to the characteristics of the environment or potential hazards. Furthermore, these advancements within the field of mobile robotics, more specifically uncrewed ground vehicles (UGVs), give the ability to potentially survey, observe, and map these inaccessible areas for humans. However, one of the most challenging areas to implement this technology is underground environments. The main challenge with implementing this technology in underground environments is the dependence on either GPS or RF communication for UGVs to navigate properly. Therefore, in order to properly demonstrate the mapping capabilities of the UGV this challenge must be resolved. The overall goal of this study is to demonstrate the mapping capabilities of a UGV while addressing this challenge and documenting the implementation and testing phase of the robot. The proposed solution to this challenge is to implement a SLAM algorithm onto the main computational device of the UGV utilizing the Robot Operating System (ROS). The algorithm is the open-source software package Slam Toolbox developed by Steve Macenski. Furthermore, the sllidar_ros2 package from Slamtec will be used to gather the lidar data from an A3M1 2D lidar. A separate program will be created to gather odometry information for our UGV robot. All of these software packages will run together in a Docker environment. Through working on this project I have developed a better understanding of the world of robotics/autonomous systems, especially with applications such as navigation and mapping. Furthermore, through this project, I have been given exposure to how research is conducted within a DOE lab setting. As robotics/autonomous systems become more advanced it's important to pursue more avenues of research such as this project as it will ensure the development of our capabilities.
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3D Reconstruction, Augmented Reality, and Telerobotic Operation - 18297
For nuclear facility decommissioning and waste cleanup, it is necessary to deploy simple and robust robots in remote sites performing precise and dexterous manipulation under teleoperation. To meet the challenge, this paper presents a new remote operation method based on augmented reality for intuitive and efficient teleoperation. The enhanced teleoperation system incorporates three technology components - 3D sensing and reconstruction, augmented reality, and teleoperation. The 3D reconstruction technology utilizes 3D cameras and constructs a 3D geometric model of the environment. Compared to the state-of-the- art technology, the presented 3D reconstruction has greater spatial precision and dynamic object tracking capability, which enhances the precision of manipulation tasks in a dynamic environment. The augmented reality technology entails generation of virtual surfaces of various geometries and dynamic characteristics, as well as consistent perceptual overlay in camera, robot and operator hand control spaces. Teleoperation is demonstrated with a dual-arm robot system operated under Robot Operating System (ROS). (authors)
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Future of Work with Robotics - 18599
The DOE Environmental Management mission continues with remaining tasks that are high-hazards to human workers and high-consequences to the nation, resulting in potentially high risks to project costs and schedules. This is the mission pull. At the same time, robotic technologies are hitting a turning point with increased productivity and reliability within society, supporting a technology push. Enabling this push are better computer processing following Moore's Law, breakthroughs in biometric and learning algorithms,and riding a wave of venture funding for intended commercialization of mechatronic and Internet of Thing (IOT) projects. There has been overall improvements in material technologies, algorithms, and software standardization with tools/libraries such as the Robot Operating System (ROS). The internet has made knowledge ubiquitous and the cell phone sector has pushed the boundaries of systems-on-chip technology. This current growth is a race between large global technology companies, and between countries that understand that there is a prize with increased commerce based on being a leader in the field of robotics and automation. This technological advances have placed this technology solidly within the next 4. Industrial Revolution being tracked by the World Economic Council. Policies and law can slow this progression down, but technological changes in adjacent fields will put additional pressure on human workers by being more economical and in saving lives. A fundamental issue is will this change be gradual or disruptive such as with the forecasted singularity. There is also a realization with automation that the transition of human workers to other fields may be temporary, but in the long run, workers may run out of viable work and long-term occupations. The obvious future of human jobs are most assured by those who can embrace the change through the design, development, installment, and maintenance of the technology. Younger workers can be re-educated while older humans can be re-trained. The goal of this paper is to explore all the forces that are enabling this revolution, investigating its many impacts, and speculating on the future of human jobs during nuclear remediation. Automation has made an impact to the manufacturing sector, and has since expanded to the retail and services sectors. The question is will this same automation transition, including robotics and artificial intelligence, occur to the environmental management and cleanup sector, and how should we prepare ourselves for this change. (author)
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Contact Control, Version 1
The contact control code is a generalized force control scheme meant to interface with a robotic arm being controlled using the Robot Operating System (ROS). The code allows the user to specify a control scheme for each control dimension in a way that many different control task controllers could be built from the same generalized controller. The input to the code includes maximum velocity, maximum force, maximum displacement, and a control law assigned to each direction and the output is a 6 degree of freedom velocity command that is sent to the robot controller.
von Sternberg, Alex↗
Contact Control, Version 1
The contact control code is a generalized force control scheme meant to interface with a robotic arm being controlled using the Robot Operating System (ROS). The code allows the user to specify a control scheme for each control dimension in a way that many different control task controllers could be built from the same generalized controller. The input to the code includes maximum velocity, maximum force, maximum displacement, and a control law assigned to each direction and the output is a 6 degree of freedom velocity command that is sent to the robot controller.
von Sternberg, Alex↗
Remote Radiation Sensing Using Aerial and Ground Platforms
Remote sensing of ionizing radiation has a significant role in waste management, nuclear material management and nonproliferation, and radiation safety. Robotic platforms can surpass the number of tasks that are achieved by humans. With this technique, the operator's radiation exposure can be decreased. Remote sensing allows for the evaluation and monitoring of radiological contamination. Gamma-ray and neutron sensors were integrated onto the robotic platforms. This approach allows for the radiation sensor data to be dynamically tracked and mapped thus enabling further analysis of the radiation flux in temporal and spatial domains. The goal is to complete scheduled tasks while the robot is being irradiated. To achieve this, electronic components must be shielded and radiation hardened. CZT Detector: Cadmium Zinc Telluride (CZT) detector technology has been a promising solution for gamma-ray and x-ray measurements. Detector data is transferred to the Odroid minicomputer that controls and powers the module via the USB. Robot Operating System (ROS) was utilized for data acquisition and data fusion. The Mariscotti method was employed for the spectrum analysis. A function was programmed in ROS for the automatic identification of photopeaks. CLYC Detector: A Cs{sub 2}LiYCl{sub 6}:Ce{sup 3+} (CLYC) detector was used for simultaneous medium-resolution gamma-ray measurements and neutron counting. A 2.54 cm diameter photomultiplier tube (PMT) was equipped with a high voltage supply and a miniature digitizer. Gamma-ray excitation: fast core-to-valence luminescence (CVL) with 1 ns decay constant, and prompt Ce{sup 3+} emission with 50 ns decay constant. Neutron excitation: slow cerium self-trapped excitation (Ce{sup 3+} STE), 1000 ns decay constant. Radiation Source Localization: Maximum Likelihood Estimation (MLE) and gradient-based methods were used to locate the position of a radiation source based on measured radiation intensities. Multi-Particle Transport Code FLUKA: Estimation of radiation damage of the electronic components is important in order to optimize the robot's operational time while it is irradiated. Displacement per atom (DPA) represents the radiation damage in materials exposed to the ionizing radiation. Various shielding layers of different thickness t were analyzed (< 5% statistical error). The model of the controller of the UAS was designed in FLUKA. Conclusion: CZT and CLYC detectors were integrated onto the robotic platforms. Radiation source localization and contour mapping using robotic platforms were studied. Functions for data analysis and fusion were developed in ROS. FLUKA code was utilized to analyze DPA values. Layers of low-density and high-density materials were used to shield the UAS electronics.
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