Reflection and Reasoning Mechanisms for Failure Detection and Recovery in a Distributed Robotic Architecture for Complex Robots

Scheutz, Matthias; Kramer, James

doi:10.1109/robot.2007.364045

Cited by 20 publications

(12 citation statements)

References 11 publications

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“…With the approach presented in this work, therefore, there is no need to explicitly identify the failure and use preprogrammed alternative behaviors, which can be difficult to design beforehand [7]. We will show that the proposed bioinspired method is able to provide high adaptability despite the extreme simplicity of the algorithm and the absence of any additional hardware to cope with failures.…”

Section: Introductionmentioning

confidence: 94%

Biologically Inspired Mobile Robot Control Robust to Hardware Failures and Sensor Noise

DallaLibera

Ikemoto

Minato

et al. 2011

RoboCup 2010: Robot Soccer World Cup XIV

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Some bacteria present a movement which can be modeled as a biased random walk. Biased random walk can be used also for artificial creatures as a very simple and robust control policy for tasks like goal reaching. In this paper, we show how a very simple control law based on random walk is able to guide mobile robot equipped with an omnidirectional camera toward a target without any knowledge about the robot’s actuators or about the robot’s camera parameters. We verified, by several simulation experiments, the robustness of the random biased control law with respect to failures of robot’s actuators or sensor damages. These damages are similar to the ones which can occur during a RoboCup match. The tests show that the optimal behavior is obtained using a bias which is roughly proportional to the random walk step, with a coefficient dependent on the physical structure of the robot, on its actuators and on and its sensors after the damage. Finally, we validated the proposed approach with experiments in the real world with a wheeled robot performing a goal reaching task in a Middle-Size RoboCup field without any prior knowledge on the actuators and without any calibration of the very noisy omnidirectional camera mounted on the robot

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Section: Introductionmentioning

confidence: 94%

Biologically Inspired Mobile Robot Control Robust to Hardware Failures and Sensor Noise

DallaLibera

Ikemoto

Minato

et al. 2011

RoboCup 2010: Robot Soccer World Cup XIV

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“…Third, the complexity of the robot required to performed effectively in each of these applications will be such that some robot autonomy, defined as the ability to carry out some function without human input (Parasuraman & Riley, 1997), will likely be necessary. We refer to such systems as autonomy-enabled robot systems, or systems in which robots autonomously perform the desired tasks with high proficiency and can often identify their own failures (Scheutz & Kramer, 2007).…”

Section: Tasks To Performmentioning

confidence: 99%

Cognitive Telepresence in Human-Robot Interactions

Harutyunyan¹,

Manohar²,

Gezehei³

et al. 2013

Journal of Human-Robot Interaction

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Remote teleoperation of advanced, semi-autonomous robotic technologies has great potential in many industries critical to the economy and for the environment of the Middle East. Applications include maintenance of under-water oil wells, maintenance of nuclear power plants, counter-terrorism and national defense, law enforcement, remote sensing, and health care. In each of these applications, a user, likely without technology expertise, must operate a complex robot in uncertain and unknown environments. The nature of the tasks and environments encountered by the robot in these applications make it highly likely that the robot's limited autonomy will fail or be insufficient to complete the desired task. In this paper, we argue that, in such scenarios, cognitive telepresence, defined as the ability of the user to comprehend and control the robot's cognition, is an important design principle for human-robot systems. We compare and contrast cognitive telepresence to existing design principles commonly discussed in the literature, and define various metrics of cognitive telepresence. Finally, via two illustrative examples and a user study, we demonstrate the usefulness of cognitive telepresence as an important design principle of human-robot systems consisting of a user with limited technology expertise and a robot with limited and error-prone artificial intelligence.

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“…[1][2][3][4][5][6] We have proposed an error recovery method using the concepts of task stratification and error classification. 7,8 In a robot system with error recovery capability, sensing is performed by using vision systems for the judgment of errors mainly at important points.…”

Section: Introductionmentioning

confidence: 99%

The Suitable Timing of Visual Sensing in Error Recovery Using Task Stratification and Error Classification

Nakamura

Nagata

Harada

et al. 2017

JRNAL

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Judgment of errors for recovery is performed during execution of the system. Ideally, it is desirable for the judgment to be performed at several times. However, in that case, many sensors would be needed and it would lead to disturbing the workflow. Therefore, it is important to be able to judge an error efficiently in the most suitable timing and within a few attempts. This paper describes a method for efficient timing of visual sensing for error recovery.

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Reflection and Reasoning Mechanisms for Failure Detection and Recovery in a Distributed Robotic Architecture for Complex Robots

Cited by 20 publications

References 11 publications

Biologically Inspired Mobile Robot Control Robust to Hardware Failures and Sensor Noise

Biologically Inspired Mobile Robot Control Robust to Hardware Failures and Sensor Noise

Cognitive Telepresence in Human-Robot Interactions

The Suitable Timing of Visual Sensing in Error Recovery Using Task Stratification and Error Classification

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