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检索条件"机构=Distributed Algorithms and Systems"

共 99 条记录，以下是31-40 订阅

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Towards 3-D distributed odor source localization: An extended graph-based formation control algorithm for plume tracking

Towards 3-D distributed odor source localization: An extende...

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IEEE/RSJ International Conference on Intelligent Robots and systems

作者： Jorge M. Soares Ali Marjovi Jonathan Giezendanner Anil Kodiyan A. Pedro Aguiar Antonio M. Pascoal Alcherio Martinoli Distributed Intelligent Systems and Algorithms Laboratory School of Architecture Civil and Environmental Engineering école Polytechnique Fédérale de Lausanne (EPFL) 1015 Switzerland Research Center for Systems and Technology Faculty of Engineering University of Porto Rua Dr. Roberto Frias 4200-465 Portugal Laboratory of Robotics and Engineering Systems Instituto Superior Técnico University of Lisbon Av. Rovisco Pais 1049-001 Lisboa Portugal

ISBN: (纸本)9781509037636

The large number of potential applications for robotic odor source localization has motivated the development of a variety of plume tracking algorithms, the majority of which work in restricted two-dimensional scenarios. In this paper, we introduce a distributed algorithm for 3-D plume tracking using a system of ground and aerial robots in formation. We propose an algorithm that takes advantage of spatially distributed measurements to track the plume in 3-D and lead the robots to the source by integrating three behaviors - upwind movement, plume centering, and Laplacian feedback formation control. We evaluate this strategy in simulation and with real robots in a wind tunnel. For a source close to the ground, results show that a team of robots running our algorithm reaches the source with low lateral error while also tracing the horizontal and vertical plume shape.

关键词： Robot sensing systems Robot kinematics Laplace equations Tracking Unmanned aerial vehicles Chemicals Manipulator sensing systems Robot kinematics Laplace's equation Position measurement plume plumes tracking Unmanned Aerial Vehicle chemical compounds Computer algorithms Robot vehicle drone honey bees Three Dimensions plume shape

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distributed graph-based convoy control for networked intelligent vehicles

Distributed graph-based convoy control for networked intelli...

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IEEE Symposium on Intelligent Vehicle

作者： Ali Marjovi Milos Vasic Joseph Lemaitre Alcherio Martinoli Distributed Intelligent Systems and Algorithms Laboratory Ecole Polytechnique Federale de Lausanne (EPFL) Lausanne Switzerland

This paper presents an approach for formation control of multi-lane vehicular convoys in highways. We extend a Laplacian graph-based, distributed control law such that networked intelligent vehicles can join or leave the formation dynamically without jeopardizing the ensemble's stability. Additionally, we integrate two essential control behaviors for lane-keeping and obstacle avoidance into the controller. To increase the performance of the convoy controller in terms of formation maintenance and fuel economy, the parameters of the controller are optimized in realistic scenarios using Particle Swarm Optimization (PSO), a powerful metaheuristic optimization method well-suited for large parameter spaces. The performances of the optimized controllers are evaluated in high-fidelity multi-vehicle simulations outlining the efficiency and robustness of the proposed strategy.

关键词： Vehicles Vehicle dynamics Collision avoidance Roads Intelligent vehicles Laplace equations

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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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An Algorithm for Formation-Based Chemical Plume Tracing Using Robotic Marine Vehicles

An Algorithm for Formation-Based Chemical Plume Tracing Usin...

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OCEANS MTS/IEEE Monterey (Conference)

作者： Jorge M. Soares A. Pedro Aguiar Antonio M. Pascoal Alcherio Martinoli Laboratory of Robotics and Engineering Systems Instituto Superior Técnico University of Lisbon Av. Rovisco Pais 1049-001 Lisboa Portugal Research Center for Systems and Technology Faculty of Engineering University of Porto Rua Dr. Roberto Frias 4200-465 Portugal Distributed Intelligent Systems and Algorithms Laboratory School of Architecture Civil and Environmental Engineering école Polytechnique Fédérale de Lausanne (EPFL) 1015 Switzerland

ISBN: (纸本)9781509015276

Robotic chemical plume tracing is a growing area of research, with envisioned real-world applications including pollution tracking, search and rescue, and ecosystem identification. However, following a chemical signal in the water is not an easy task due to the nature of chemical transport and to limitations in sensing and communication. In this paper, we propose an approach for near-surface waterborne plume tracing using a combined team of autonomous surface and underwater vehicles. All vehicles are equipped with appropriate chemical sensors and acoustic modems. The team moves in a triangular formation, while using the flow direction and the samples obtained to steer the group along the plume. Leader vehicles at the surface implement a formation controller based on Laplacian feedback while the underwater vehicle performs acoustic ranging to the leaders. The solution was evaluated using a CFD simulation of a freshwater plume and a calibrated dynamic model of the MEDUSA autonomous marine vehicles. The group is able to move in a stable formation, sample the salinity, and trace the plume to its source.

关键词： Vehicles Chemicals Robots Ocean temperature Sea surface Salinity (geophysical) Underwater vehicles

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Vision-based Unmanned Aerial Vehicle detection and tracking for sense and avoid systems

Vision-based Unmanned Aerial Vehicle detection and tracking ...

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IEEE/RSJ International Conference on Intelligent Robots and systems

作者： Krishna Raj Sapkota Steven Roelofsen Artem Rozantsev Vincent Lepetit Denis Gillet Pascal Fua Alcherio Martinoli Computer Vision Laboratory School of Communication and Computer Sciences école Polytechnique Fédérale de Lausanne (EPFL) Switzerland Distributed Intelligent Systems and Algorithms Laboratory School of Architecture Civil and Environmental Engineering EPFL Switzerland Institute for Computer Graphics and Vision TU Graz Austria Coordination and Interaction System Group School of Engineering EPFL Switzerland

ISBN: (纸本)9781509037636

We propose an approach for on-line detection of small Unmanned Aerial Vehicles (UAVs) and estimation of their relative positions and velocities in the 3D environment from a single moving camera in the context of sense and avoid systems. This problem is challenging both from a detection point of view, as there are no markers on the targets available, and from a tracking perspective, due to misdetection and false positives. Furthermore, the methods need to be computationally light, despite the complexity of computer vision algorithms, to be used on UAVs with limited payload. To address these issues we propose a multi-staged framework that incorporates fast object detection using an AdaBoost-based approach, coupled with an on-line visual-based tracking algorithm and a recent sensor fusion and state estimation method. Our framework allows for achieving real-time performance with accurate object detection and tracking without any need of markers and customized, high-performing hardware resources.

关键词： Target tracking Object detection Collision avoidance Cameras Visualization Detectors

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Lily: A miniature floating robotic platform for programmable stochastic self-assembly

Lily: A miniature floating robotic platform for programmable...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Bahar Haghighat Emmanuel Droz Alcherio Martinoli Distributed Intelligent Systems and Algorithms Laboratory Ecole Polytechnique Federale de Lausanne Switzerland

ISBN: (纸本)9781479969241

Fluid-mediated programmable stochastic self-assembly offers promising means to formation of target structures capable of a variety of functionalities. While miniaturized building blocks allow for finer resolutions in such structures, as well as access to unconventional environments, they can only be endowed with very limited on-board resources. In this paper we present the design, fabrication, and experimental results validating the key functionalities of the Lily robot as the building block in a programmable stochastic fluidic self-assembly system, capable of forming 2D structures. In particular, we aim at driving a system including an arbitrary number of Lilies to form target structures through parallel self-assembly, using exclusively local information and communication. While capable of wireless communication to a base station, Lilies are endowed with custom-designed electropermanent magnets to latch and also to communicate locally with their neighbors. Several experiments validate the reliability of the radio channel as well as the robustness of the local induction-based communication which allows for data transfer at 9600 bps with a success rate of 92.8% without repetition. The latches are shown to hold four times the weight of a single robot and to drag in another Lily from a distance of 4 mm in water.

关键词： Robot sensing systems Robot kinematics Latches Base stations Batteries Self-assembly

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SwarmViz: An open-source visualization tool for Particle Swarm Optimization

SwarmViz: An open-source visualization tool for Particle Swa...

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Congress on Evolutionary Computation

作者： Guillaume Jornod Ezequiel Di Mario Iñaki Navarro Alcherio Martinoli Distributed Intelligent Systems and Algorithms Laboratory Ecole Polytechnique Fédérale de Lausanne

Particle Swarm Optimization (PSO) is a metaheuristic for solving high dimensional optimization problems. Due to the large number of dimensions usually employed with PSO, it is not trivial to visualize and monitor the progress of the algorithm. Because of this, adjusting the parameters that govern the dynamics of the swarm for a specific problem becomes challenging. In this article, we present SwarmViz, an open-source visualization tool for PSO. Through SwarmViz, users are able to set up PSO experiments on canonical benchmark functions or input data from external experiments (e.g., learning robotic controllers), and to visualize the optimization process with state-of-the-art visualization tools. SwarmViz has two main goals. First, to enable researchers to monitor the progress of their specific optimization problem and adjust the relevant PSO parameters. Second, to give a visual insight about PSO to students in the scope of teaching optimization techniques. We demonstrate the features of the software through examples on well-known numerical benchmark functions and a case study on the optimization of a robotic controller.

关键词： Optimization Visualization

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A distributed formation-based odor source localization algorithm - design, implementation, and wind tunnel evaluation

A distributed formation-based odor source localization algor...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Jorge M. Soares A. Pedro Aguiar António M. Pascoal Alcherio Martinoli Laboratory of Robotics and Systems in Engineering and Science University of Lisbon Lisboa Portugal Distributed Intelligent Systems and Algorithms Laboratory Ecole Polytechnique Fédérale de Lausanne (EPFL) Lausanne Switzerland Faculty of Engineering University of Porto Research Center for Systems and Technology Porto Portugal

ISBN: (纸本)9781479969241

Robotic odor source localization is a promising tool with numerous applications in safety, search and rescue, and environmental science. In this paper, we present an algorithm for odor source localization using multiple cooperating robots equipped with chemical sensors. Laplacian feedback is employed to maintain the robots in a formation, introducing spatial diversity that is used to better establish the position of the flock relative to the plume and its source. Robots primarily move upwind but use odor information to adjust their position and spacing so that they are centered on the plume and trace its structure. Real-world experiments were performed with an ethanol plume inside a wind tunnel, and used to both validate the algorithm and assess the impact of different formation shapes.

关键词： Robot sensing systems Robot kinematics Algorithm design and analysis Shape Hardware

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distributed Deconfliction Algorithm for Unmanned Aerial Vehicles with Limited Range and Field of View Sensors

Distributed Deconfliction Algorithm for Unmanned Aerial Vehi...

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American Control Conference

作者： Steven Roelofsen Alcherio Martinoli Denis Gillet Distributed Intelligent Systems and Algorithms Laboratory School of Architecture Civil and Environmental Engineering Ecole Polytechnique Federale de Lausanne Coordination and Interaction System Group School of Engineering Ecole Polytechnique Federale de Lausanne

ISBN: (纸本)9781479917730

This paper proposes a novel approach for collision avoidance between Unmanned Aerial Vehicles (UAVs) with limited range and field of view sensors. The algorithm is designed for unicycle vehicles that need to fly above a specific minimal speed to maintain flight. It uses a navigation function approach when the UAV is clear from conflict and smoothly switches to a collision avoidance maneuver when other UAVs are encountered. We show that the proposed avoidance algorithm can ensure a collision-free path. We also carry out a throughout quantitative analysis of the algorithm singularities and propose heuristic recipes for avoiding deadlock situations. Simulations are performed to show the effectiveness of the algorithm.

关键词： Collision avoidance Sensors Aircraft Turning Aircraft navigation Mathematical model

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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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