Conference Paper

Enhanced teleoperation for D&D

Argonne National Laboratory, Lemont, Illinois, United States
DOI: 10.1109/ROBOT.2004.1308836 Conference: Robotics and Automation, 2004. Proceedings. ICRA '04. 2004 IEEE International Conference on, Volume: 4
Source: IEEE Xplore

ABSTRACT Remote systems are essential for reducing risk to human workers from hazardous radiation and difficult work environments, while improving productivity and reducing costs. The major drawback of currently available remote manipulator systems is that teleoperation is slow and imprecise. The presented work focuses on enhancing remote operation of tools for D&D tasks by introducing teleautonomy and telecollaboration. In teleautonomy, the robot performs a given task autonomously, while the human operator intervenes in the process as a supervisor. In telecollaboration, the human operator is passively constrained by a virtual fixture, but is responsible for the motion. This work, sponsored by the US Department of Energy (DOE) Environmental Management Science Program (EMSP), builds on a reactive, agent-based control architecture and robot control technology.


Available from: Michael Peshkin, May 06, 2015
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Purpose – Sets out to discuss lessons learned from the creation and use of an over-the-internet teleoperation testbed. Design/methodology/approach – Seven lessons learned from the testbed are presented. Findings – This teleoperation interface improves task performance, as proved by a single demonstration. Originality/value – In helping to overcome time-delay difficulties in the operation, leading to dramatically improved task performance, this study contributes significantly to the improvement of teleoperation by making better use of human skills.
    Industrial Robot 04/2006; 33(3):187-193. DOI:10.1108/01439910610659097 · 0.62 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Future space explorations necessitate manipulation of space structures in support of extra vehicular activities or extraterrestrial resource exploitation. In these tasks robots are expected to assist or replace human crew to alleviate human risk and enhance task performance. However due to the vastly unstructured and unpredictable environmental conditions, automation of robotic task is virtually impossible and thus teleoperation is expected to be employed. However teleoperation is extremely slow and inefficient. To improve task efficiency of teleoperation, this work introduces semi-autonomous telerobotic operation technology. Key technological innovations include implementation of reactive agent based robotic architecture and enhanced operator interface that renders virtual fixture.
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: This dissertation addresses the development of a telemanipulation system using intelligent mapping from a haptic user interface to a remote manipulator to assist in maximizing the manipulation capabilities of persons with disabilities. This mapping, referred to as assistance function, is determined on the basis of environmental model or real-time sensory data to guide the motion of a telerobotic manipulator while performing a given task. Human input is enhanced rather than superseded by the computer. This is particularly useful when the user has restricted range of movements due to certain disabilities such as muscular dystrophy, a stroke, or any form of pathological tremor. In telemanipulation system, assistance of variable position/velocity mapping or virtual fixture can improve manipulation capability and dexterity. Conventionally, these assistances are based on the environment information, without knowing user's motion intention. In this dissertation, user's motion intention is combined with real-time environment information for applying appropriate assistance. If the current task is following a path, a virtual fixture orthogonal to the path is applied. Similarly, if the task is to align the end-effector with a target, an attractive force field is generated. In order to successfully recognize user's motion intention, a Hidden Markov Model (HMM) is developed. Also this dissertation describes the HMM based skill learning and its application in a motion therapy system in which motion along a labyrinth is controlled using a haptic interface. Two persons with disabilities on upper limb are trained using this virtual therapist. The performance measures before and after the therapy training, including the smoothness of the trajectory, distance ratio, time taken, tremor and impact forces are presented. The results demonstrate that the forms of assistance provided reduced the execution times and increased the performance of the chosen tasks for the disabled individuals. In addition, these results suggest that the introduction of the haptic rendering capabilities, including the force feedback, offers special benefit to motion-impaired users by augmenting their performance on job related tasks.