Figure 11 - uploaded by Neal A Yancey
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Radiation scan using RGL&IID in TAN 616 Operating Pump Room Note: Each cross hair represents a separate scanning point. The color of the cross hair indicates the radiation level that correlates to the scale below the graph. The units are in total counts in a given 10-second scan time
Source publication
The United States Department of Energy (DOE) continually seeks safer and more cost-effective technologies for use in decontaminating and decommissioning nuclear facilities. To this end, the Deactivation and Decommissioning Focus Area of DOE's Office of Science and Technology sponsors Large-Scale Demonstration and Deployment Projects (LSDDP) to test...
Contexts in source publication
Context 1
... the RGL&IID demonstration, 11 scans were made. The location of these scans is shown in Figure 11 by the bold numbers (1-11). Each of the 11 scans was composed of several point measurements that ranged from 9 to 25 points. ...
Citations
... The mode and degree of human-robot interaction vary considerably (see [5] for review). Robot operations in the teleoperation mode of human-robot communication require continuous low-level inputs from humans; as a result, even slight lapses in communications can degrade performance substantially, and the workload of the human operator can be undesirably high (e.g., [17], [18]). At the other extreme, autonomous robots that operate without any human input often perform complex tasks poorly compared to robots that collaborate with humans interactively (e.g., [19], [20], [21]). ...
We generalize precisiated natrual language by establishing a formal logic as a generalized precisiation language. In this formal logic, each proposition has a form that reflects a syntactic structure observed in natural language. Various syntactic structures are incorporated in the formal logic so that it precisiates not only perceptual propositions but also action-related propositions. The syntax of the formal logic allows us to create infinitely many precisiated propositions while ensuring that every proposition in it is precisiated. We discuss how our formal logic can eectively mediate human-robot interaction.
... Many existing robot nuclear characterisation systems are tethered, single robot systems [1], [2] and [3]. To speed up mapping and increase system fault tolerance it might be more appropriate to use multiple robots in which wireless network technologies rather than tethers are employed (despite interference or noise caused by radiation) as demonstrated in [4] and [5]. While a wireless system may allow increased system flexibility and reduce inter-robot space conflict issues, a wireless robot is constrained by the need to periodically return to a recharging station to recharge its battery. ...
Efficient control strategies for robot systems cannot always be developed by hand, especially when the robot system is operating in an unknown or uncertain environment. In this paper we show how the Reinforcement Learning (RL) technique might be applied to improve the efficiency of a mobile robot in a nuclear decommissioning characterisation, in particular allowing it to learn efficient routes back to a recharging station. We implement this learning functionality in a mobile agent (MA) environment. By doing so we can make use of the positive characteristics of MA mobility such as adaptability, fault tolerance and dynamic positioning of learning or control in a distributed system to supplement learning. Experimental results show how RL provides a more efficient method in this task than a non-AI control approach.
... Characterisation may occur in unstructured environments with restricted access, and unknown geographical layout, physical, or radiological contents. Existing robot characterisation systems include the Internal Duct Characterisation System (IDCS) [2], Remote Underwater Characterisation System (RUCS) [3], Mobile Autonomous Characterisation System (MACS) [4], Pioneer [5], and the Robotic Gamma Locating and Isotopic Identification Device (RGL&IID) [6]. These systems are mainly electrically powered, tethered and tele-operated by human operators although MACS uses Radio Communication/Autonomous Navigation and RGL&IID Wireless LAN Communication. ...
Nuclear decommissioning involves the characterisation of hazardous and contaminated environments. Robot characterisation systems have been developed to reduce the risk to human operatives, however their efficiency is limited. Coming decades will see a substantial increase in decommissioning globally as a large number of nuclear facilities are due to reach the end of their useful life. It is desirable that robot characterisation systems meet this increase in demand by becoming more efficient. This paper describes an architecture that makes use of advances in computer science including mobile agent technology, which we believe will offer improved efficiency over existing robot characterisation systems.
... A nationwide attempt to accelerate cleanup efforts at DOE sites has given rise to an unprecedented need to remotely characterize buildings that have been marked for decontamination and decommissioning. Although, teleoperated robotic solutions offer significant benefits in terms of human exposure, time, cost and quality of data, close evaluation of these operations brings to light severe limitations to the master-slave strategy employed, including lapses in communication and situation awareness, which result in damage to the environment, loss of or damage to the robot, requiring personnel to enter the environment [1], [2]. As mechanical 'subordinates,' such teleoperated robots are dependent on continuous, low-level input from a human and are poorly equipped to cope with communication failures or changes in operator workload. ...
We submit that the most interesting and fruitful human-robot interaction (HRI) may be possible when the robot is able to interact with the human as a true team member, rather than a tool. However, the benefits of shared control can all too easily be overshadowed by challenges inherent to blending human and robot initiative. The most important requirements for peer-peer interaction are system trust and ability to predict system behavior. The human must be able to understand the reason for and effects of robot initiative. These requirements can only be met through careful application of human factors principles and usability testing to determine how users interact with the system. This paper discusses the recent human participant usability testing, which took our current implementation to task using a search and rescue scenario within a complex, real-world environment. The purpose of testing was to examine how human operators work with the robotic system at each level of autonomy, and how interaction with the robot should be structured to enable situation awareness and task completion. Analyses revealed that our architecture equally supported situation awareness and target detection by novices and experts, although experienced users were more likely to have more performance expectations of the interface. Results also had implications regarding the ability of participants to effectively utilize the collaborative workspace and, most importantly, their ability to understand and willingness to accept robot initiative.
... As part of the FY 2000 and 2001 Department of Energy Large-Scale Demonstration and Deployment Project (LSDDP), the INEEL collaborated with the Russian Research and Development Institute of Construction Technology (NIKIMT) to develop a novel robotic solution to the problem of characterizing radiation in a remote environment. The resulting Robotic Gamma Locating and Isotopic Identification Device (RGL&IID) integrated DOE Robotics Crosscutting (Rbx) technology with NIKIMT Russian gamma locating and isotopic identification technology [1]. While the new robotic solution offered significant improvements in terms of time, cost, worker exposure and the quality of data acquired, the remote nature of this new technology presented new human-robot interaction challenges. ...
... As part of the FY 2000 and 2001 LSDDP, the Idaho National Engineering and Environmental Laboratory (INEEL) collaborated with the Russian Research and Development Institute of Construction Technology (NIKIMT). This collaboration resulted in the development of the Robotic Gamma Locating and Isotopic Identification Device (RGL&IID) which integrates DOE Robotics Crosscutting (Rbx) technology with NIKIMT Russian gamma locating and isotopic identification technology [1]. While the new robotic solution offered significant improvements in terms of time, cost, worker exposure and the quality of data acquired, the remote nature of this new technology presented new human-robot interaction challenges. ...
Remote characterization of high radiation environments is a pressing application area where robots can provide benefits in terms of time, cost, safety and quality of data. However, the DOE roadmap for Robotics and Intelligent Machines states that `usability' may well prove to be the most challenging and yet crucial component of robotic systems for remote characterization and handling of radioactive and hazardous materials. In 2001, the INEEL successfully deployed a teleoperated robotic system coupled with a Gamma Locating and Isotopic Identification Device (RGL&IID) to characterize an area that had been closed to human entry for many years. This paper examines the human-robot dynamic of this teleoperated task and the limitations inherent to the master-slave strategy employed. Next, the paper outlines an innovative, mixed-initiative command and control architecture developed to address these limitations. The resulting, mixed-initiative control architecture retains the human in the loop, but interleaves multiple levels of human intervention into the functioning of a robotic system that can, in turn, scale its own level of initiative to meet whatever level of input is handed down.
... A nationwide attempt to accelerate cleanup efforts at DOE sites has given rise to an unprecedented need to remotely characterize buildings that have been marked for decontamination and decommissioning. Although, teleoperated robotic solutions offer significant benefits in terms of human exposure, time, cost and quality of data, close evaluation of these operations brings to light severe limitations to the master-slave strategy employed, including lapses in communication and situation awareness, which result in damage to the environment, loss of or damage to the robot, requiring personnel to enter the environment [1], [2]. As mechanical 'subordinates,' such teleoperated robots are dependent on continuous, low-level input from a human and are poorly equipped to cope with communication failures or changes in operator workload. ...
We develop a formal logic for task descriptions that are easy to interpret for both humans and robots. Tasks are described in propositional forms that reflect syntactic structures observed in natural language so that all the resulting task descriptions can be easily understood by humans. At the same time, these propositional forms ensure that each task description is interpretable by robots. Infinitely many task descriptions can be created in this formal logic so that the formal logic can support complex human-robot interactions. We establish a hierarchy of propositions that enhances the expressive power, the interactivity, and the deductive apparatus of our formal logic. We also examine how to systematically evaluate the feasibility of each task description using the formal logic.
