67 research outputs found

    Distributed Fault-Tolerant Control for Networked Robots in the Presence of Recoverable/Unrecoverable Faults and Reactive Behaviors

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    The paper presents an architecture for distributed control of multi-robot systems with an integrated fault detection, isolation, and recovery strategy. The proposed solution is based on a distributed observer-controller schema where each robot, by communicating only with its direct neighbors, is able to estimate the overall state of the system; such an estimate is then used by the controllers of each robot to achieve global missions as, for example, centroid and formation tracking. The information exchanged among the observers is also used to compute residual vectors that allow each robot to detect failures on anyone of the teammates, even if not in direct communication. The proposed strategy considers both recoverable and unrecoverable actuator faults as well as it properly manages the possible activation of reactive local control behaviors of the robots (e.g., the activation of obstacle avoidance strategy), which generate control inputs different from those required by the global mission control. In particular, when the robots are subject to recoverable faults, those are managed at a local level by computing a proper compensating control action. On the other side, when the robots are subject to unrecoverable faults, the faults are isolated from anyone of the teammates by means of a distributed fault detection and isolation strategy; then, the faulty robots are removed from the team and the mission is rearranged. The proposed strategy is validated via numerical simulations where the system properly identifies and manages the different cases of recoverable and unrecoverable actuator faults, as well as it manages the activation of local reactive control in an integrated case study

    Experiments of Formation Control With Multirobot Systems Using the Null-Space-Based Behavioral Control

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    Ultrasound imaging classifications of thyroid nodules for malignancy risk stratification and clinical management : state of the art

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    Assessing the risk of malignancy in the thyroid with ultrasound (US) is crucial in patients with nodules, as it can aid in selecting those who should have a fine-needle aspiration (FNA) biopsy performed. Many studies have examined whether the US characteristics of thyroid nodules are useful indicators of histological malignancy. Overall, these investigations have identified a few US features that are significantly more frequent in malignant thyroid nodules which can be coalesced into a defining set to be used as an indicator of a higher risk of malignancy. Despite these efforts, none of these classifications have been widely adopted worldwide, and there are still conflicting recommendations from different institutions. Understanding the role and appropriate utilization of these systems could facilitate the effective interpretation and communication of thyroid US findings among referring physicians and radiologists. In this comprehensive review, we outline the major US classification systems of thyroid nodules published in the last few years

    A decentralized fault detection and isolation strategy for networked robots

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    This paper presents a distributed Fault Detection and Isolation (FDI) strategy, applied in conjunction with a distributed controller-observer schema, for a team of networked robots. Differently from other works in literature, the proposed FDI approach makes each robot of the team able to detect and isolate input faults of other robots even if not directly connected to it. The residual dynamics of the FDI observers are analytically investigated, and adaptive thresholds are derived to avoid the occurrence of false alarms in the presence of nonzero initial observer estimation errors. The approach is validated via numerical simulations in the case of time-varying centroid and formation control tasks

    Distributed fault detection and recovery for networked robots

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    The paper deals with the problem of decentralized fault detection, isolation and recovery for teams of networked robots. The proposed strategy is a combination of distributed and local approaches that allow the robots to deal with both recoverable and unrecoverable faults. A local adaptive fault observer is used to locally compensate recoverable faults, while a distributed fault detection and isolation strategy is used to allow each robot to detect unrecoverable faults on other teammates even if not directly connected; once the faulty robots have been isolated, they are removed from the team and the mission is rearranged. Results of numerical simulations and experiments involving a team of 5 mobile robots are provided to show the effectiveness of the approach

    How to Investigate Constraints and Motions in Assemblies by Screw Theory

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    The use of the screw theory to do constraint analysis is described. Screw theory uses a matrix representation to describe, for any mating features, the part's degrees of freedom (twist-matrix) and the directions along which the constraint reacts (wrench-matrix). From these screw-matrices it is possible to individuate the exact constraint conditions of parts into the assembly. Starting from the basics of this theory, how to get screw parameters (constrained directions and degrees of freedom) from screw-matrices is analyzed and how to make the constraint analysis for several serial and parallel constraint configurations is described. Finally, a MATLAB algorithm to analyze possible constraints and motions in assemblies with any complexity is presented

    Distributed fault-tolerant strategy for networked robots with both cooperative and reactive controls

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    The paper presents a controller-observer architecture with decentralized fault tolerance strategy for a networked team of autonomous robots. In the proposed architecture, each robot runs a decentralized observer to estimate the overall system state and a distributed control law for centroid and formation tracking control. The decentralized observer is used to compute a set of residuals in charge of detecting and isolating actuator faults affecting the other robots, even if not directly connected. The fault detection strategy is designed so as to distinguish between actuator faults and activation of local reactive controls e.g., to manage the presence of obstacles. The strategy is validated via numerical simulations
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