Fault detection and identification in a mobile robot using multiple model estimation and neural network

Goel, Puneet; Dedeoǧlu, Göksel; Roumeliotis, Stergios I.; Sukhatme, Gaurav S.

doi:10.1109/robot.2000.846370

Cited by 109 publications

(46 citation statements)

References 12 publications

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“…In [122], the authors propose to analyze the residuals of a bank of Kalman Filters using thresholds to determine if one filter is diverging. A similar approach is described in [123] but the decision part is given to a Neural Network. Sundvall and Jensfelt, in [124], add a coherence measure between different estimations.…”

Section: B Avoiding or Reducing The Impact Of Driftmentioning

confidence: 99%

Simultaneous Localization and Mapping: A Survey of Current Trends in Autonomous Driving

Bresson

Alsayed

et al. 2017

IEEE Trans. Intell. Veh.

705

366

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Abstract-In this article, we propose a survey of the Simultaneous Localization And Mapping field when considering the recent evolution of autonomous driving. The growing interest regarding self-driving cars has given new directions to localization and mapping techniques. In this survey, we give an overview of the different branches of SLAM before going into the details of specific trends that are of interest when considered with autonomous applications in mind. We first present the limits of classical approaches for autonomous driving and discuss the criteria that are essential for this kind of application. We then review the methods where the identified challenges are tackled. We mostly focus on approaches building and reusing long-term maps in various conditions (weather, season, etc.). We also go through the emerging domain of multi-vehicle SLAM and its link with self-driving cars. We survey the different paradigms of that field (centralized and distributed) and the existing solutions. Finally, we conclude by giving an overview of the various largescale experiments that have been carried out until now and discuss the remaining challenges and future orientations.

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Section: B Avoiding or Reducing The Impact Of Driftmentioning

confidence: 99%

Simultaneous Localization and Mapping: A Survey of Current Trends in Autonomous Driving

Bresson

Alsayed

et al. 2017

IEEE Trans. Intell. Veh.

705

366

View full text Add to dashboard Cite

show abstract

“…Many studies have been devoted to endogenous fault detection, that is, a robot detecting faults in itself, see for instance [6,7,8,9,10,11,12,13,14]. Some faults are, however, hard to detect in the robot in which they occur.…”

Section: Introductionmentioning

confidence: 99%

From Fireflies to Fault-Tolerant Swarms of Robots

Christensen

O’Grady

Dorigo

2009

IEEE Trans. Evol. Computat.

141

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Abstract. One of the essential benefits of multi-robot systems is redundancy. In case one robot breaks down, another robot can take steps to repair the failed robot or take over the failed robot's task. Although fault tolerance and robustness to individual failures have often been central arguments in favor of multi-robot systems, few studies have been dedicated to the subject. In this study, we take inspiration from the synchronized flashing behavior observed in some species of fireflies. We derive a completely distributed algorithm to detect non-operational individuals in a multi-robot system. Each robot flashes by lighting up its onboard LEDs and neighboring robots are driven to flash in synchrony. Since robots that are suffering catastrophic failures do not flash periodically, they can be detected by operational robots. We explore the performance of the proposed algorithm both on a real world multirobot system and in simulation. We show that failed robots are detected correctly and in a timely manner, and we show that a system composed of robots with simulated self-repair capabilities can survive relatively high failure rates.

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“…This study deals with the most common used serial, open chained and rigid robot manipulator and only a detailed review on this type of robots is given here. Studies on other type robots can be found in (Goel et al, 2000;Tinós & Terra, 2002). Most studies on FDI for robot manipulators are based on nonlinear observer approaches.…”

Section: Literature Overview Of Model-based Fdi For Nonlinear Systemsmentioning

confidence: 99%

Model-Based FDI Schemes For Robot Manipulators Using Soft Computing Techniques

Yüksel¹,

Sezgin²

2010

Fault Detection

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Fault detection and identification in a mobile robot using multiple model estimation and neural network

Cited by 109 publications

References 12 publications

Simultaneous Localization and Mapping: A Survey of Current Trends in Autonomous Driving

Simultaneous Localization and Mapping: A Survey of Current Trends in Autonomous Driving

From Fireflies to Fault-Tolerant Swarms of Robots

Model-Based FDI Schemes For Robot Manipulators Using Soft Computing Techniques

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