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Ryad Benosman - One of the best experts on this subject based on the ideXlab platform.

  • Neuromorphic Event-Based Generalized Time-Based Stereovision.
    Frontiers in Neuroscience, 2018
    Co-Authors: Sio-hoi Ieng, Joao Carneiro, Marc Osswald, Ryad Benosman
    Abstract:

    3D reconstruction from multiple viewpoints is an important problem in machine vision that allows recovering tridimensional structures from multiple two-dimensional views of a given scene. Reconstruction from multiple views is conventionally achieved through a process of pixel luminance-based matching between different views. Unlike conventional machine vision methods that solve matching ambiguities by operating only on spatial constraints and luminance, this paper introduces a full time-based solution to stereovision using the high temporal resolution of neuromorphic asynchronous event-based cameras. These cameras output dynamic visual information and luminance encoded in time. They allow a formulation of stereovision as a pure event coincidence detection problem. We will introduce a methodology for time based stereovision in the context of binocular and trinocular configurations using time based event matching criterion combining for the first time all together: space, time, luminance and motion.

  • Neuromorphic Event-Based Generalized Time-Based Stereovision
    Frontiers in Neuroscience, 2018
    Co-Authors: Sio-hoi Ieng, Joao Carneiro, Marc Osswald, Ryad Benosman
    Abstract:

    3D reconstruction from multiple viewpoints is an important problem in machine vision that allows recovering tridimensional structures from multiple two-dimensional views of a given scene. Reconstructions from multiple views are conventionally achieved through a process of pixel luminance-based matching between different views. Unlike conventional machine vision methods that solve matching ambiguities by operating only on spatial constraints and luminance, this paper introduces a fully time-based solution to stereovision using the high temporal resolution of neuromorphic asynchronous event-based cameras. These cameras output dynamic visual information in the form of what is known as " change events " that encode the time, the location and the sign of the luminance changes. A more advanced event-based camera, the Asynchronous Time-based Image Sensor (ATIS), in addition of change events, encodes absolute luminance as time differences. The stereovision problem can then be formulated solely in the time domain as a problem of events coincidences detection problem. This work is improving existing event-based stereovision techniques by adding luminance information that increases the matching reliability. It also introduces a formulation that does not require to build local frames (though it is still possible) from the luminances which can be costly to implement. Finally, this work also introduces a methodology for time based stereovision in the context of binocular and trinocular configurations using time based event matching criterion combining for the first time all together: space, time, luminance, and motion.

  • Asynchronous visual event-based time-to-contact
    Frontiers in Neuroscience, 2014
    Co-Authors: Xavier Clady, Sio-hoi Ieng, Charles Clercq, Fouzhan Houseini, Marco Randazzo, Lorenzo Natale, Chiara Bartolozzi, Ryad Benosman
    Abstract:

    Reliable and fast sensing of the environment is a fundamental requirement for autonomous mobile robotic platforms. Unfortunately, the frame-based acquisition paradigm at the basis of main stream artificial perceptive systems is limited by low temporal dynamics and redundant data flow, leading to high computational costs. Hence, conventional sensing and relative computation are obviously incompatible with the design of high speed sensor-based reactive control for mobile applications, that pose strict limits on energy consumption and computational load. This paper introduces a fast obstacle avoidance method based on the output of an asynchronous event-based time encoded imaging sensor. The proposed method relies on an event-based Time To Contact (TTC) computation based on visual event-based motion flows. The approach is event-based in the sense that every incoming event adds to the computation process thus allowing fast avoidance responses. The method is validated indoor on a mobile robot, comparing the event-based TTC with a laser range finder TTC, showing that event-based sensing offers new perspectives for mobile robotics sensing.

Sio-hoi Ieng - One of the best experts on this subject based on the ideXlab platform.

  • Neuromorphic Event-Based Generalized Time-Based Stereovision.
    Frontiers in Neuroscience, 2018
    Co-Authors: Sio-hoi Ieng, Joao Carneiro, Marc Osswald, Ryad Benosman
    Abstract:

    3D reconstruction from multiple viewpoints is an important problem in machine vision that allows recovering tridimensional structures from multiple two-dimensional views of a given scene. Reconstruction from multiple views is conventionally achieved through a process of pixel luminance-based matching between different views. Unlike conventional machine vision methods that solve matching ambiguities by operating only on spatial constraints and luminance, this paper introduces a full time-based solution to stereovision using the high temporal resolution of neuromorphic asynchronous event-based cameras. These cameras output dynamic visual information and luminance encoded in time. They allow a formulation of stereovision as a pure event coincidence detection problem. We will introduce a methodology for time based stereovision in the context of binocular and trinocular configurations using time based event matching criterion combining for the first time all together: space, time, luminance and motion.

  • Neuromorphic Event-Based Generalized Time-Based Stereovision
    Frontiers in Neuroscience, 2018
    Co-Authors: Sio-hoi Ieng, Joao Carneiro, Marc Osswald, Ryad Benosman
    Abstract:

    3D reconstruction from multiple viewpoints is an important problem in machine vision that allows recovering tridimensional structures from multiple two-dimensional views of a given scene. Reconstructions from multiple views are conventionally achieved through a process of pixel luminance-based matching between different views. Unlike conventional machine vision methods that solve matching ambiguities by operating only on spatial constraints and luminance, this paper introduces a fully time-based solution to stereovision using the high temporal resolution of neuromorphic asynchronous event-based cameras. These cameras output dynamic visual information in the form of what is known as " change events " that encode the time, the location and the sign of the luminance changes. A more advanced event-based camera, the Asynchronous Time-based Image Sensor (ATIS), in addition of change events, encodes absolute luminance as time differences. The stereovision problem can then be formulated solely in the time domain as a problem of events coincidences detection problem. This work is improving existing event-based stereovision techniques by adding luminance information that increases the matching reliability. It also introduces a formulation that does not require to build local frames (though it is still possible) from the luminances which can be costly to implement. Finally, this work also introduces a methodology for time based stereovision in the context of binocular and trinocular configurations using time based event matching criterion combining for the first time all together: space, time, luminance, and motion.

  • Asynchronous visual event-based time-to-contact
    Frontiers in Neuroscience, 2014
    Co-Authors: Xavier Clady, Sio-hoi Ieng, Charles Clercq, Fouzhan Houseini, Marco Randazzo, Lorenzo Natale, Chiara Bartolozzi, Ryad Benosman
    Abstract:

    Reliable and fast sensing of the environment is a fundamental requirement for autonomous mobile robotic platforms. Unfortunately, the frame-based acquisition paradigm at the basis of main stream artificial perceptive systems is limited by low temporal dynamics and redundant data flow, leading to high computational costs. Hence, conventional sensing and relative computation are obviously incompatible with the design of high speed sensor-based reactive control for mobile applications, that pose strict limits on energy consumption and computational load. This paper introduces a fast obstacle avoidance method based on the output of an asynchronous event-based time encoded imaging sensor. The proposed method relies on an event-based Time To Contact (TTC) computation based on visual event-based motion flows. The approach is event-based in the sense that every incoming event adds to the computation process thus allowing fast avoidance responses. The method is validated indoor on a mobile robot, comparing the event-based TTC with a laser range finder TTC, showing that event-based sensing offers new perspectives for mobile robotics sensing.

Cameron Nowzari - One of the best experts on this subject based on the ideXlab platform.

  • Robust Dynamic Event-Triggered Coordination With a Designable Minimum Inter-Event Time
    arXiv: Optimization and Control, 2019
    Co-Authors: James Berneburg, Cameron Nowzari
    Abstract:

    This paper revisits the classical multi-agent average consensus problem for which many different event-triggered control strategies have been proposed over the last decade. Many of the earliest versions of these works conclude asymptotic stability without proving that Zeno behavior, or deadlocks, do not occur along the trajectories of the system. More recent works that resolve this issue either: (i) propose the use of a dwell-time that forces inter-event times to be lower-bounded away from zero but sacrifice asymptotic convergence in exchange for practical convergence (or convergence to a neighborhood); (ii) guarantee non-Zeno behaviors and asymptotic convergence but do not provide a positive minimum inter-event time guarantee; or (iii) are not fully distributed. Additionally, the overwhelming majority of these works provide no form of robustness analysis on the event-triggering strategy. More specifically, if arbitrarily small disturbances can remove the non-Zeno property then the theoretically correct algorithm may not actually be implementable. Instead, this work for the first time presents a fully distributed, robust, dynamic event-triggered algorithm, for general directed communication networks, for which a desired positive minimum inter-event time can be chosen by each agent in a distributed fashion. Simulations illustrate our results.

  • ACC - Distributed Dynamic Event-Triggered Coordination with a Designable Minimum Inter-Event Time
    2019 American Control Conference (ACC), 2019
    Co-Authors: James Berneburg, Cameron Nowzari
    Abstract:

    This paper revisits the classical multi-agent average consensus problem for which many different event-triggered control strategies have been proposed over the last decade. Many of the early versions of these works conclude asymptotic stability without proving that Zeno behavior, or deadlocks, do not occur along the trajectories of the system. More recent works that have studied this issue fall short in that they either: (i) propose the use of a dwell-time that forces inter-event times to be lower-bounded away from 0 but sacrifices asymptotic convergence in exchange for practical convergence (or convergence to a neighborhood; (ii) guarantee non-Zeno behaviors and asymptotic convergence but without a positive minimum inter-event time guarantee; or (iii) are not fully distributed. Instead, this work for the first time presents a fully distributed event-triggering algorithm for which a desired minimum inter-event time can be chosen by each agent while still guaranteeing asymptotic convergence to the average consensus state. Simulations illustrate our results.

Linlin Qin - One of the best experts on this subject based on the ideXlab platform.

  • Finite-time event-triggered control for switched systems with time-varying delay
    2016 Chinese Control and Decision Conference (CCDC), 2016
    Co-Authors: Linlin Qin, Xinghua Liu, Shi Chun
    Abstract:

    In this paper, the problem of finite-time stabilization is considered for switched linear systems with time-varying delay and norm-bounded exogenous disturbance under the event-triggered control scheme. First by employing a full-dimension state observer, an observer-based event-triggered controller is designed. Then based on Lyapunov-like function method and average dwell time technique, some sufficient conditions are given to to guarantee the finite-time stability of the resulting dynamic augmented closed-loop system. A numerical example is finally exploited to verify the effectiveness and potential of the achieved control scheme.

  • Finite-time event-triggered H∞ control for switched systems with time-varying delay
    Neurocomputing, 2016
    Co-Authors: Xinghua Liu, Linlin Qin
    Abstract:

    This paper considers the problem of finite-time event-triggered H ∞ control for switched linear systems with time-varying delay and norm-bounded exogenous disturbance. First by employing a state observer, an observer-based event-triggered controller is designed to guarantee the finite-time stabilization of the resulting dynamic augmented closed-loop system. Then based on Lyapunov-like function method and average dwell time technique, some sufficient conditions are given to ensure the finite-time stabilization of the H ∞ control system. A numerical example is finally exploited to verify the effectiveness and potential of the achieved control scheme.

Jong-tae Lim - One of the best experts on this subject based on the ideXlab platform.

  • supervisory control of real time discrete event systems under bounded time constraints
    IEE Proceedings - Control Theory and Applications, 2004
    Co-Authors: Seongjin Park, Kwang-hyun Cho, Jong-tae Lim
    Abstract:

    An analytical framework for supervisory control of real-time discrete event systems (DESs) under bounded time constraints is presented. In order to address the bounded time constraints of the systems, timed languages based on timed transition models are introduced. Using eligible time bounds, the notions of trace-controllability and time-controllability of timed languages are proposed. Based on these notions, necessary and sufficient conditions for the existence of a supervisor for a real-time DES to achieve the given timed language specification are presented. The proposed approach shows that an exhaustive enumeration of the language generated in timed transition models is not needed to verify such existence conditions of the supervisor.