79 research outputs found

    Position / force control of systems subjected to communicaton delays and interruptions in bilateral teleoperation

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    Thesis (Master)--Izmir Institute of Technology, Mechanical Engineering, Izmir, 2012Includes bibliographical references (leaves: 65-68)Text in English; Abstract: Turkish and Englishix, 76 leavesTeleoperation technology allows to remotely operate robotic (slave) systems located in hazardous, risky and distant environments. The human operator sends commands through the controller (master) system to execute the tasks from a distance. The operator is provided with necessary (visual, audio or haptic) feedback to accomplish the mission remotely. In bilateral teleoperation, continuous feedback from the remote environment is generated. Thus, the operator can handle the task as if the operator is in the remote environment relying on the relevant feedback. Since teleoperation deals with systems controlled from a distance, time delays and package losses in transmission of information are present. These communication failures affect the human perception and system stability, and thus, the ability of operator to handle the task successfully. The objective of this thesis is to investigate and develop a control algorithm, which utilizes model mediated teleoperation integrating parallel position/force controllers, to compensate for the instability issues and excessive forcing applied to the environment arising from communication failures. Model mediation technique is extended for three-degrees-of-freedom teleoperation and a parallel position/force controller, impedance controller, is integrated in the control algorithm. The proposed control method is experimentally tested by using Matlab Simulink blocksets for real-time experimentation in which haptic desktop devices, Novint Falcon and Phantom Desktop are configured as master and slave subsystems of the bilateral teleoperation. The results of these tests indicate that the stability and passivity of proposed bilateral teleoperation systems are preserved during constant and variable time delays and data losses while the position and force tracking test results provide acceptable performance with bounded errors

    Design of a Bio-Inspired 3D Orientation Coordinate System and Application in Robotised Tele-Sonography

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    A learning-based shared control architecture for interactive task execution

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    Shared control is a key technology for various robotic applications in which a robotic system and a human operator are meant to collaborate efficiently. In order to achieve efficient task execution in shared control, it is essential to predict the desired behavior for a given situation or context to simplify the control task for the human operator. To do this prediction, we use Learning from Demonstration (LfD), which is a popular approach for transferring human skills to robots. We encode the demonstrated behavior as trajectory distributions and generalize the learned distributions to new situations. The goal of this paper is to present a shared control framework that uses learned expert distributions to gain more autonomy. Our approach controls the balance between the controller’s autonomy and the human preference based on the distributions of the demonstrated trajectories. Moreover, the learned distributions are autonomously refined from collaborative task executions, resulting in a master-slave system with increasing autonomy that requires less user input with an increasing number of task executions. We experimentally validated that our shared control approach enables efficient task executions. Moreover, the conducted experiments demonstrated that the developed system improves its performances through interactive task executions with our shared control

    Intent-Recognition-Based Traded Control for Telerobotic Assembly over High-Latency Telemetry

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    As we deploy robotic manipulation systems into unstructured real-world environments, the tasks which those robots are expected to perform grow very quickly in complexity. These tasks require a greater number of possible actions, more variable environmental conditions, and larger varieties of objects and materials which need to be manipulated. This in turn leads to a greater number of ways in which elements of a task can fail. When the cost of task failure is high, such as in the case of surgery or on-orbit robotic interventions, effective and efficient task recovery is essential. Despite ever-advancing capabilities, however, the current and near future state-of-the-art in fully autonomous robotic manipulation is still insufficient for many tasks in these critical applications. Thus, successful application of robotic manipulation in many application domains still necessitates a human operator to directly teleoperate the robots over some communications infrastructure. However, any such infrastructure always incurs some unavoidable round-trip telemetry latency depending on the distances involved and the type of remote environment. While direct teleoperation is appropriate when a human operator is physically close to the robots being controlled, there are still many applications in which such proximity is infeasible. In applications which require a robot to be far from its human operator, this latency can approach the speed of the relevant task dynamics, and performing the task with direct telemanipulation can become increasingly difficult, if not impossible. For example, round-trip delays for ground-controlled on-orbit robotic manipulation can reach multiple seconds depending on the infrastructure used and the location of the remote robot. The goal of this thesis is to advance the state-of-the art in semi-autonomous telemanipulation under multi-second round-trip communications latency between a human operator and remote robot in order to enable more telerobotic applications. We propose a new intent-recognition-based traded control (IRTC) approach which automatically infers operator intent and executes task elements which the human operator would otherwise be unable to perform. What makes our approach more powerful than the current approaches is that we prioritize preserving the operator's direct manual interaction with the remote environment while only trading control over to an autonomous subsystem when the operator-local intent recognition system automatically determines what the operator is trying to accomplish. This enables operators to perform unstructured and a priori unplanned actions in order to quickly recover from critical task failures. Furthermore, this thesis also describes a methodology for introducing and improving semi-autonomous control in critical applications. Specifically, this thesis reports (1) the demonstration of a prototype system for IRTC-based grasp assistance in the context of transatlantic telemetry delays, (2) the development of a systems framework for IRTC in semi-autonomous telemanipulation, and (3) an evaluation of the usability and efficacy of that framework with an increasingly complex assembly task. The results from our human subjects experiments show that, when incorporated with sufficient lower-level capabilities, IRTC is a promising approach to extend the reach and capabilities of on-orbit telerobotics and future in-space operations

    Elicitation of trustworthiness requirements for highly dexterous teleoperation systems with signal latency

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    IntroductionTeleoperated robotic manipulators allow us to bring human dexterity and cognition to hard-to-reach places on Earth and in space. In long-distance teleoperation, however, the limits of the speed of light results in an unavoidable and perceivable signal delay. The resultant disconnect between command, action, and feedback means that systems often behave unexpectedly, reducing operators' trust in their systems. If we are to widely adopt telemanipulation technology in high-latency applications, we must identify and specify what would make these systems trustworthy.MethodsIn this requirements elicitation study, we present the results of 13 interviews with expert operators of remote machinery from four different application areas—nuclear reactor maintenance, robot-assisted surgery, underwater exploration, and ordnance disposal—exploring which features, techniques, or experiences lead them to trust their systems.ResultsWe found that across all applications, except for surgery, the top-priority requirement for developing trust is that operators must have a comprehensive engineering understanding of the systems' capabilities and limitations. The remaining requirements can be summarized into three areas: improving situational awareness, facilitating operator training, and familiarity, and easing the operator's cognitive load.DiscussionWhile the inclusion of technical features to assist the operators was welcomed, these were given lower priority than non-technical, user-centric approaches. The signal delays in the participants' systems ranged from none perceived to 1 min, and included examples of successful dexterous telemanipulation for maintenance tasks with a 2 s delay. As this is comparable to Earth-to-orbit and Earth-to-Moon delays, the requirements discussed could be transferable to telemanipulation tasks in space

    The Effects of Pictorial Realism, Delay of Visual Feedback, and Observer Interactivity on the Subjective Sense of Presence

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    Two experiments examined the effects of pictorial realism, observer interactivity, and delay of visual feedback on the sense of presence. Subjects were presented pairs of virtual enviornments (a simulated driving task) that differed in one or more ways from each other. After subjects had completed the second member of each pair they reported which of the two had produced the greater amount of presence and indicated the size of this difference by means of a 1-100 scale. As predicted, realism and interactivity increased presence while delay of visual feedback diminished it. According to subjects\u27 verbal responses to a postexperiment interview, pictorial realism was the least influential of the three variables examined. Further, although some subjects reported an increase in the sense of presence over the course of the experiment, most said it reamined unchanged or became weaker

    Mitigating User Frustration through Adaptive Feedback based on Human-Automation Etiquette Strategies

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    The objective of this study is to investigate the effects of feedback and user frustration in human-computer interaction (HCI) and examine how to mitigate user frustration through feedback based on human-automation etiquette strategies. User frustration in HCI indicates a negative feeling that occurs when efforts to achieve a goal are impeded. User frustration impacts not only the communication with the computer itself, but also productivity, learning, and cognitive workload. Affect-aware systems have been studied to recognize user emotions and respond in different ways. Affect-aware systems need to be adaptive systems that change their behavior depending on users’ emotions. Adaptive systems have four categories of adaptations. Previous research has focused on primarily function allocation and to a lesser extent information content and task scheduling. However, the fourth approach, changing the interaction styles is the least explored because of the interplay of human factors considerations. Three interlinked studies were conducted to investigate the consequences of user frustration and explore mitigation techniques. Study 1 showed that delayed feedback from the system led to higher user frustration, anger, cognitive workload, and physiological arousal. In addition, delayed feedback decreased task performance and system usability in a human-robot interaction (HRI) context. Study 2 evaluated a possible approach of mitigating user frustration by applying human-human etiquette strategies in a tutoring context. The results of Study 2 showed that changing etiquette strategies led to changes in performance, motivation, confidence, and satisfaction. The most effective etiquette strategies changed when users were frustrated. Based on these results, an adaptive tutoring system prototype was developed and evaluated in Study 3. By utilizing a rule set derived from Study 2, the tutor was able to use different automation etiquette strategies to target and improve motivation, confidence, satisfaction, and performance using different strategies, under different levels of user frustration. This work establishes that changing the interaction style alone of a computer tutor can affect a user’s motivation, confidence, satisfaction, and performance. Furthermore, the beneficial effect of changing etiquette strategies is greater when users are frustrated. This work provides a basis for future work to develop affect-aware adaptive systems to mitigate user frustration
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