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


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.

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Available from: Michael Peshkin, Oct 03, 2015
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    • "What is required is powerful operator aid which can expand the operator's ability to guide efficient and precise manipulation. In this regards, joint R&D activities have been conducted at Argonne National Laboratroy and Northwestern University to facilitate two types of enhancements: semi-automatic teleoperation technologies that blends teleoperation with autonomous behaviors (Park 2004), and enhances user interface to attain efficient robotic actions (Faulring, 2004; Dejong, 2004). Such enhanced telerobotic manipulation technologies, although originally developed and demonstrated for D&D (decontamination and decommissioning) of nuclear facilities, share common basis with the application needs in space programs. "
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    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.
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    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.
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    ABSTRACT: Die in dieser Arbeit vorgestellten Verfahren ermöglichen eine Verbesserung der Leistungsfähigkeit und Wirklichkeitsnähe von haptischen Telepräsenzsystemen durch den Einsatz eines Mensch-Maschine-Kooperationsschemas. Das Ziel besteht darin, den Operator durch lokale Intelligenz des Teleoperators in der Durchführung von telepräsenten Arbeiten zu unterstützen. Dadurch sollen die Verluste bzgl. Performanz und Transparenz, die wegen technischer Unzulänglichkeiten des Telepräsenzsystems unvermeidlich sind, ausgeglichen werden. Der Arbeit liegt die Erkenntnis zugrunde, dass heutige Roboter einfache Manipulationsaufgaben autonom präziser durchführen können als ein Mensch. Dadurch ist die Grundlage für eine effektive Kooperation zwischen Mensch und Roboter gegeben, bei der die menschlichen Fähigkeiten zur verantwortungsvollen, flexiblen und kreativen Aufgabenplanung mit der Fähigkeit des Roboters, präzise Manipulationen ermüdungsfrei durchzuführen, kombiniert werden. Bei der vorgestellten Lösung ist es nicht erforderlich, dass der Mensch diese Aufgabenteilung explizit steuert, sondern es findet eine natürliche Kooperation zwischen Mensch und Roboter statt. Zur wirksamen Assistenz müssen drei Voraussetzungen erfüllt sein: 1. Die Manipulationsaufgabe, die der Operator durchzuführen beabsichtigt, muss vom Teleoperator geschätzt werden. 2. Der Teleoperator muss einen präzisen Plan zur Durchführung seiner Aufgabe haben. 3. die Bewegungen des Operators müssen mit den vom Teleoperator geplanten Bewegungen in Einklang gebracht werden können. Diese drei Problemstellungen werden in der vorliegenden Arbeit eingehend betrachtet. Zur Bestimmung der Manipulationsabsicht wird ein modellbasierter Schätzer verwendet. Dieser steht in Wechselwirkung zu einer bildbasierten Erkennung der Zielumgebung, die zur Aufgabenplanung verwendet wird. Schließlich werden die Bewegungen von einem Passivität gewährleistenden Regler fusioniert.
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