HUMAN MACHINE COOPERATIVE TELEROBOTICS

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The remediation and deactivation and decommissioning (D&D) of nuclear waste storage tanks using telerobotics is one of the most challenging tasks faced in environmental cleanup. Since a number of tanks have reached the end of their design life and some of them have leaks, the unstructured, uncertain and radioactive environment makes the work inefficient and expensive. However, the execution time of teleoperation consumes ten to hundred times that of direct contact with an associated loss in quality. Thus, a considerable effort has been expended to improve the quality and efficiency of telerobotics by incorporating into teleoperation and robotic control functions ... continued below

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Hamel, William R.; Douglass, Spivey; Kim, Sewoong; Murray, Pamela; Shou, Yang; Sridharan, Sriram et al. June 30, 2003.

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Description

The remediation and deactivation and decommissioning (D&D) of nuclear waste storage tanks using telerobotics is one of the most challenging tasks faced in environmental cleanup. Since a number of tanks have reached the end of their design life and some of them have leaks, the unstructured, uncertain and radioactive environment makes the work inefficient and expensive. However, the execution time of teleoperation consumes ten to hundred times that of direct contact with an associated loss in quality. Thus, a considerable effort has been expended to improve the quality and efficiency of telerobotics by incorporating into teleoperation and robotic control functions such as planning, trajectory generation, vision, and 3-D modeling. One example is the Robot Task Space Analyzer (RTSA), which has been developed at the Robotics and Electromechanical Systems Laboratory (REMSL) at the University of Tennessee in support of the D&D robotic work at the Oak Ridge National Laboratory and the National Energy Technology Laboratory. This system builds 3-D models of the area of interest in task space through automatic image processing and/or human interactive manual modeling. The RTSA generates a task plan file, which describes the execution of a task including manipulator and tooling motions. The high level controller of the manipulator interprets the task plan file and executes the task automatically. Thus, if the environment is not highly unstructured, a tooling task, which interacts with environment, will be executed in the autonomous mode. Therefore, the RTSA not only increases the system efficiency, but also improves the system reliability because the operator will act as backstop for safe operation after the 3-D models and task plan files are generated. However, unstructured conditions of environment and tasks necessitate that the telerobot operates in the teleoperation mode for successful execution of task. The inefficiency in the teleoperation mode led to the research described as Human Machine Cooperative Telerobotics (HMCTR). The HMCTR combines the telerobot with robotic control techniques to improve the system efficiency and reliability in teleoperation mode. In this topical report, the control strategy, configuration and experimental results of Human Machines Cooperative Telerobotics (HMCTR), which modifies and limits the commands of human operator to follow the predefined constraints in the teleoperation mode, is described. The current implementation is a laboratory-scale system that will be incorporated into an engineering-scale system at the Oak Ridge National Laboratory in the future.

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  • Report No.: None
  • Grant Number: AR26-97FT34315
  • DOI: 10.2172/894296 | External Link
  • Office of Scientific & Technical Information Report Number: 894296
  • Archival Resource Key: ark:/67531/metadc881707

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  • June 30, 2003

Added to The UNT Digital Library

  • Sept. 22, 2016, 2:13 a.m.

Description Last Updated

  • Jan. 9, 2018, 1:07 p.m.

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Hamel, William R.; Douglass, Spivey; Kim, Sewoong; Murray, Pamela; Shou, Yang; Sridharan, Sriram et al. HUMAN MACHINE COOPERATIVE TELEROBOTICS, report, June 30, 2003; Tennessee. (digital.library.unt.edu/ark:/67531/metadc881707/: accessed November 17, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.