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检索条件"机构=Distributed Intelligent Systems and Algorithms"

共 86 条记录，以下是31-40 订阅

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An Experimental Study in Wireless Connectivity Maintenance Using up to 40 Robots Coordinated by an Institutional Robotics Approach

An Experimental Study in Wireless Connectivity Maintenance U...

引用

IEEE/RSJ International Conference on intelligent Robots and systems

作者： Jose N. Pereira Porfirio Silva Pedro U. Lima Alcherio Martinoli Distributed Intelligent Systems and Algorithms Laboratory EPFL Lausanne Switzerland Institute for Systems and Robotics Instituto Superior Técnico Lisbon Portugal

ISBN: (纸本)9781467363563

This work is developed in the framework of Institutional Robotics (IR), an approach to cooperative distributed robotic systems that draws inspiration from the social sciences. We consider a case study concerned with a swarm of simple robots which has to maintain wireless connectivity and a certain degree of spatial compactness. Robots have local, bounded communication capabilities and have to execute the task (running an IR controller) using exclusively as information their current number of wireless connections to neighbors. For the very same case study, we previously introduced an IR-based macroscopic model for the behavior of a large number of robots, validated using a submicroscopic model implemented through a realistic simulator. In this work, we go a step further and validate our submicroscopic model with real world experiments, duplicating accurately the conditions used, including a large number of robots and noisy communication channels. The main conclusions of this paper are two-fold. First, the IR approach was able to maintain the wireless connectivity of a swarm of 40 real, resource-constrained robots. This speaks in favor of the robustness and scalability of such approach. Second, the submicroscopic model implemented is faithfully capturing the reality and can be used to further optimize the performances of distributed control strategies using an IR approach.

关键词： IR reality can be used Wireless connectivity Robot Reality iridium dike swarms robotics role model

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A distributed Source Term Estimation Algorithm for Multi-Robot systems

A Distributed Source Term Estimation Algorithm for Multi-Rob...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Faezeh Rahbar Alcherio Martinoli Distributed Intelligent Systems and Algorithms Laboratory École Polytechnique Fédérale de Lausanne (EPFL) Lausanne Switzerland

ISBN: (数字)9781728173955

ISBN: (纸本)9781728173962

Finding sources of airborne chemicals with mobile sensing systems finds applications in safety, security, and emergency situations related to medical, domestic, and environmental domains. Given the often critical nature of all the applications, it is important to reduce the amount of time necessary to accomplish this task through intelligent systems and algorithms. In this paper, we extend a previously presented algorithm based on source term estimation for odor source localization for homogeneous multi-robot systems. By gradually increasing the level of coordination among multiple mobile robots, we study the benefits of a distributed system on reducing the amount of time and resources necessary to achieve the task at hand. The method has been evaluated systematically through high-fidelity simulations and in a wind tunnel emulating realistic and repeatable conditions in different coordination scenarios and with different number of robots.

关键词： Robot kinematics Robot sensing systems Estimation Navigation Probabilistic logic

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Enhancing measurement quality through active sampling in mobile air quality monitoring sensor networks

Enhancing measurement quality through active sampling in mob...

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IEEE/ASME (AIM) International Conference on Advanced intelligent Mechatronics

作者： Adrian Arfire Ali Marjovi Alcherio Martinoli Distributed Intelligent Systems and Algorithms Laboratory École Polytechnique Fédérale de Lausanne (EPFL) Lausanne Switzerland

ISBN: (纸本)9781509020669

In recent years, a growing number of research groups have targeted the development and deployment of networks using low-cost chemical sensors for monitoring air quality. Due to economical reasoning, most of these systems make use of some sort of mobility to increase spatial coverage. The effect of mobility on measurement quality has, however, been largely neglected. The long response time of the chemical sensors typically used for this type of application, in conjunction with platform mobility, leads to significant signal distortion. While this problem can be addressed through signal deconvolution techniques, their effectiveness is limited by the typical poor Signal-to-Noise Ratio (SNR) of the measured signal. In this paper, we study the possibility of enhancing the measurement quality of chemical sensors through the use of active sampling (or sniffing). We propose different sniffer designs, employing both fans and pumps as actuators. Using a rigorous experimental framework, inside a wind tunnel, we study the ability of active samplers to increase measurement SNR, and thus indirectly to improve sensor dynamic response. We obtain a significant and consistent improvement in SNR for one of our pump-based sniffer designs. Finally, we validate the robustness of this signal enhancement in real-world conditions through an outdoor car-based experiment.

关键词： Robot sensing systems Atmospheric measurements Pollution measurement Fans Mobile communication Signal to noise ratio Air quality

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A Collaborative Sensor Fusion Algorithm for Multi-object Tracking Using a Gaussian Mixture Probability Hypothesis Density Filter

A Collaborative Sensor Fusion Algorithm for Multi-object Tra...

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International Conference on intelligent Transportation

作者： Milos Vasic Alcherio Martinoli Distributed Intelligent Systems and Algorithms Laboratory Ecole Polytechnique Fédérale de Lausanne (EPFL) Lausanne Switzerland

This paper presents a method for collaborative tracking of multiple vehicles that extends a Gaussian Mixture Probability Hypothesis Density (GM-PHD) filter with a collaborative fusion algorithm. Measurements are preprocessed in a detect-before-track fashion, and cars are tracked using a rectangular shape model. The proposed method successfully mitigates clutter and occlusion problems. In order to extend the field of view of individual vehicles and increase the estimation confidence in the areas where a target is observable by multiple vehicles, PHD intensities are exchanged between vehicles and fused in the Collaborative GM-PHD filter using a novel algorithm based on the Generalized Covariance Intersection. The method is extensively evaluated using a calibrated, high-fidelity simulator in scenarios where vehicles exhibit both straight and curved motion at different speeds.

关键词： Collaboration Target tracking Robot sensing systems Automobiles Approximation methods Shape

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distributed graph-based control of convoys of heterogeneous vehicles using curvilinear road coordinates

Distributed graph-based control of convoys of heterogeneous ...

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International Conference on intelligent Transportation

作者： Iñaki Navarro Florian Zimmermann Milos Vasic Alcherio Martinoli Distributed Intelligent Systems and Algorithms Laboratory Ecole Polytechnique Fédérale de Lausanne (EPFL) Lausanne Switzerland

This paper investigates the problem of controlling a heterogeneous group of vehicles with the aim of forming multilane convoys. We use a distributed, graph-based control law, implemented in a longitudinal coordinate system parallel to the road. Each vehicle maintains a local graph with information from only nearby vehicles, in which the desired distances between vehicles are calculated dynamically. This allows for fast adaptation to the changes in the number of vehicles and their positions. We have also implemented a distributed mechanism that allows vehicles to change lane in a cooperative way within the convoy. Systematic experiments have been carried out in a high-fidelity simulator in order to show the performance of the proposed control law.

关键词： Roads Safety Laplace equations Fuels Automobiles Shape

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distributed Spatiotemporal Suppression for Environmental Data Collection in Real-World Sensor Networks

Distributed Spatiotemporal Suppression for Environmental Dat...

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IEEE International Conference on distributed Computing in Sensor systems

作者： William C. Evans Alexander Bahr Alcherio Martinoli Distributed Intelligent Systems and Algorithms Laboratory Ecole Polytechnique Fédérale de Lausanne (EPFL) Lausanne Switzerland

ISBN: (纸本)9781479902064

Environmental processes are often severely over-sampled. As sensor networks become more ubiquitous for this purpose, increasing network longevity becomes ever more important. Radio transceivers in particular are a great source of energy consumption, and many networking algorithms have been proposed that seek to minimize their use. Traditionally, such approaches are often data agnostic, i.e., their performance is not dependent on the properties of the data they transport. In this paper we explore algorithms that exploit environmental relationships in order to reduce the amount of transmitted data while maintaining expected levels of accuracy. We employ a realistic testing environment for evaluating the power savings brought by such algorithms, based on Sensorscope, a commercial sensor network product for environmental monitoring. We implement and test a suppression-based data collection algorithm from literature that to our knowledge has never been implemented on a real system, and propose modifications that make it more suitable for real-world conditions. Using a custom extension board developed for in situ power monitoring, we show that while the algorithms greatly reduce the amount of energy spent on transmitting packets, they have no effect on the real system's overall power consumption due to its preexisting network architecture.

关键词： Environmental processes Sensor Networks purpose ecological processes Sensor networks energy consumption Data Collection Methods Energy sources algorithms attribute data NETWORK STRUCTURE Environmental data

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Simulation Experiments with Bio-inspired algorithms for Odor Source Localization in Laminar Wind Flow

Simulation Experiments with Bio-inspired Algorithms for Odor...

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International Conference on Machine Learning and Applications (ICMLA)

作者： Thomas Lochmatter Alcherio Martinoli Distributed Intelligent Systems and Algorithms Laboratory (DISAL) École Polytechnique Fédérale de Lausanne Lausanne Switzerland

We compare three bio-inspired odor source localization algorithm (casting, surge-spiral and surge-cast) for environments with a main wind flow in simulation. The wind flow is laminar and the simulation setup similar to the setup in the wind tunnel in which we have carried out similar experiments with real robots. The algorithms are compared in terms of success rate and distance overhead when tracking the plume up to the source. We conclude that the algorithms based on upwind surge yield significantly better performance than pure casting.

关键词： Surges Casting Robot sensing systems Service robots Machine learning algorithms Machine learning intelligent systems intelligent structures Learning systems Chemical sensors

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distributed Particle Swarm Optimization - particle allocation and neighborhood topologies for the learning of cooperative robotic behaviors

Distributed Particle Swarm Optimization - particle allocatio...

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IEEE/RSJ International Conference on intelligent Robots and systems

作者： I. Navarro E. Di Mario A. Martinoli Distributed Intelligent Systems and Algorithms Laboratory School of Architecture Civil and Environmental Engineering Ecole Poly technique Federale de Lausanne

In this article we address the automatic synthesis of controllers for the coordinated movement of multiple mobile robots, as a canonical example of cooperative robotic behavior. We use five distributed noise-resistant variations of Particle Swarm Optimization (PSO) to learn in simulation a set of 50 weights of an artificial neural network. They differ on the way the particles are allocated and evaluated on the robots, and on how the PSO neighborhood is implemented. In addition, we use a centralized approach that allows for benchmarking with the distributed versions. Regardless of the learning approach, each robot measures locally and individually the performance of the group using exclusively on-board resources. Results show that four of the distributed variations obtain similar fitnesses as the centralized version, and are always able to learn. The other distributed variation fails to properly learn on some of the runs, and results in lower fitness when it succeeds. We test systematically the controllers learned in simulation in real robot experiments.

关键词： Robot kinematics Mobile robots Robot sensing systems Collision avoidance Measurement Particle swarm optimization

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Collision avoidance with limited field of view sensing: A velocity obstacle approach

Collision avoidance with limited field of view sensing: A ve...

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2017 IEEE International Conference on Robotics and Automation, ICRA 2017

作者： Roelofsen, Steven Gillet, Denis Martinoli, Alcherio Distributed Intelligent Systems and Algorithms Laboratory School of Architecture Civil and Environmental Engineering École Polytechnique Fédérale de Lausanne United States Coordination and Interaction System Group School of Engineering École Polytechnique Fédérale de Lausanne United States

ISBN: (纸本)9781509046331

Collision avoidance, in particular between robots, is an important component for autonomous robots. It is a necessary component in numerous applications such as humanrobot interaction, automotive or unmanned aerial vehicles. While many collision avoidance algorithms take into account actuation constraints, only a few consider sensing limitations. In this paper, we present a reciprocal collision avoidance algorithm based on the velocity obstacle approach that guarantees collision-free maneuvers even when the robots are only capable to sense their environment within a limited Field Of View (FOV). We also present the challenges associated to sensors with limited FOV, show the conditions under which maneuvering can be safely done, and the modifications that a velocity obstacle approach requires to satisfy such conditions. We provide simulations and real robot experiments to validate our approach. © 2017 IEEE.

关键词： Collision avoidance

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Graph based distributed control of non-holonomic vehicles endowed with local positioning information engaged in escorting missions

Graph based distributed control of non-holonomic vehicles en...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Riccardo Falconi Sven Gowal Alcherio Martinoli Dipartimento di Elettronica Universita di Bologna Italy Distributed Intelligent Systems and Algorithms Laboratory Ecole Polytechnique Federale de Lausanne Switzerland

Using graph theory, this paper investigates how a group of robots, endowed with local positioning (range and bearing from other robots), can be engaged in a leader-following mission whilst keeping a predefined configuration. The possibility to locally change the behaviors of the follower team to accomodate both tasks is explored. In particular, a methodology to automatically adjust the parameters of the inter-robot interactions and a nonlinear PI controller are explained and implemented. Our approach is supported by a mathematical analysis as well as real robot experiments.

关键词： distributed control Vehicles Robots Robotics and automation Graph theory USA Councils Automatic control Mathematical analysis Multiagent systems Communication networks

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