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

共 86 条记录，以下是21-30 订阅

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Characterization and validation of a novel robotic system for fluid-mediated programmable stochastic self-assembly

Characterization and validation of a novel robotic system fo...

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IEEE/RSJ International Conference on intelligent Robots and systems

作者： Bahar Haghighat Alcherio Martinoli Distributed Intelligent Systems and Algorithms Laboratory School of Architecture Civil and Environmental Engineering école Polytechnique Fédérale de Lausanne Switzerland

ISBN: (纸本)9781509037636

Several self-assembly systems have been developed in recent years, where depending on the capabilities of the building blocks and the controlability of the environment, the assembly process is guided typically through either a fully centralized or a fully distributed control approach. In this work, we present a novel experimental system for studying the range of fully centralized to fully distributed control strategies. The system is built around the floating 3-cm-sized Lily robots, and comprises a water-filled tank with peripheral pumps, an overhead camera, an overhead projector, and a workstation capable of controlling the fluidic flow field, setting the ambient luminosity, communicating with the robots over radio, and visually tracking their trajectories. We carry out several experiments to characterize the system and validate its capabilities. First, a statistical analysis is conducted to show that the system is governed by reaction diffusion dynamics, and validate the applicability of the standard chemical kinetics modeling. Additionally, the natural tendency of the system for structure formation subject to different flow fields is investigated and corresponding implications on guiding the self-assembly process are discussed. Finally, two control approaches are studied: 1) a fully distributed control approach and 2) a distributed approach with additional central supervision exhibiting an improved performance. The formation time statistics are compared and a discussion on the generalization of the method is provided.

关键词： Stochastic processes Wireless communication Robot sensing systems Process control Decentralized control Trajectory

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On-Board Vision-Based 3D Relative Localization System for Multiple Quadrotors

On-Board Vision-Based 3D Relative Localization System for Mu...

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IEEE International Conference on Robotics and Automation

作者： Duarte Dias Rodrigo Ventura Pedro Lima Alcherio Martinoli Distributed Intelligent Systems and Algorithms Laboratory School of Architecture Civil and Environmental Engineering école Polytechnique Fédérale de Lausanne Switzerland

ISBN: (纸本)9781467380270

This work proposes a novel relative localization system, based on active markers and an on-board camera, for tracking multiple quadrotors in a limited field of view. The system extracts the 3D poses of the markers including one that, by pulsating at a predefined frequency, provides an unique platform ID. We discuss how the camera field of view can be explored in presence of multiple targets, and what are the conditions on the system visibility that lead to the establishment of bidirectional sensing between robots with similar sensing capabilities. A visibility analysis is conducted to show that the developed relative localization system meets such requirements, and a closed-loop experiment is used to validate its performance under these conditions. Finally, its performance is compared with other results from the literature, and a metric is established with the intent of mapping different design solutions, facilitating design choices in presence of different requirements.

关键词： Multiple Quadrotors presence different requirements

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A system implementation and evaluation of a cooperative fusion and tracking algorithm based on a Gaussian Mixture PHD filter

A system implementation and evaluation of a cooperative fusi...

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IEEE/RSJ International Conference on intelligent Robots and systems

作者： Milos Vasic David Mansolino Alcherio Martinoli Distributed Intelligent Systems and Algorithms Laboratory School of Architecture Civil and Environmental Engineering école Polytechnique Fédérale de Lausanne (EPFL) Switzerland

ISBN: (纸本)9781509037636

This paper focuses on a real system implementation, analysis, and evaluation of a cooperative sensor fusion algorithm based on a Gaussian Mixture Probability Hypothesis Density (GM-PHD) filter, using simulated and real vehicles endowed with automotive-grade sensors. We have extended our previously presented cooperative sensor fusion algorithm with a fusion weight optimization method and implemented it on a vehicle that we denote as the ego vehicle. The algorithm fuses information obtained from one or more vehicles located within a certain range (that we call cooperative), which are running a multi-object tracking PHD filter, and which are sharing their object estimates. The algorithm is evaluated on two Citroen C-ZERO prototype vehicles equipped with Mobileye cameras for object tracking and lidar sensors from which the ground truth positions of the tracked objects are extracted. Moreover, the algorithm is evaluated in simulation using simulated C-ZERO vehicles and simulated Mobileye cameras. The ground truth positions of tracked objects are in this case provided by the simulator. Multiple experimental runs are conducted in both simulated and real-world conditions in which a few legacy vehicles were tracked. Results show that the cooperative fusion algorithm allows for extending the sensing field of view, while keeping the tracking accuracy and errors similar to the case in which the vehicles act alone.

关键词： Vehicles Radar tracking Cameras Sensor fusion Laser radar Algorithm design and analysis Robot sensing systems

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Environmental Field Estimation with Hybrid-Mobility Sensor Networks

Environmental Field Estimation with Hybrid-Mobility Sensor N...

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IEEE International Conference on Robotics and Automation

作者： William C. Evans Duarte Dias Steven Roelofsen Alcherio Martinoli Distributed Intelligent Systems and Algorithms Laboratory School of Architecture Civil and Environmental Engineering Ecole Polytechnique Fédérale de Lausanne 1015 Lausanne Switzerland

ISBN: (纸本)9781467380270

The remarkable accessibility of modern flying robots makes them an attractive platform for environmental sensing. However, low cost and ease of use are currently incompatible with large payloads, severely limiting the choice of sensor and ultimately modality. This paper describes the design of a system for using a small infrared thermometer to estimate the surface temperature over an area that is large compared to the area measured by the sensor, by mounting it on a flying robot. We leverage a priori knowledge about the spatial statistics of the phenomena under measure in order to plan an informative sampling path, fusing observations by Gaussian process regression. Our approach is designed to be evaluated in an indoor testbed, in which a quadrotor, in cooperation with simulated static sensing nodes, estimates the spatial distribution of surface temperature over a controlled thermal gradient. We perform extensive systematic experimentation both in simulation and our real-world testbed environment, with our algorithm estimating surface temperature to an accuracy of up to 2.1 °C over a 16 m~2 area ranging in value from 25-65 °C.

关键词： Estimation Hybrid-Mobility Sensor

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Graph-based distributed control for adaptive multi-robot patrolling through local formation transformation

Graph-based distributed control for adaptive multi-robot pat...

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IEEE/RSJ International Conference on intelligent Robots and systems

作者： Alicja Wasik Jose N. Pereira Rodrigo Ventura Pedro U. Lima Alcherio Martinoli Distributed Intelligent Systems and Algorithms Laboratory School of Architecture Civil and Environmental Engineering école Polytechnique Fédérale de Lausanne Switzerland Institute for Systems and Robotics Instituto Superior Técnico Universidade de Lisboa Portugal

ISBN: (纸本)9781509037636

Multi-robot cooperative navigation in real-world environments is essential in many applications, including surveillance and search-and-rescue missions. State-of-the-art methods for cooperative navigation are often tested in ideal laboratory conditions and not ready to be deployed in real-world environments, which are often cluttered with static and dynamic obstacles. In this work, we explore a graph-based framework to achieve control of real robot formations moving in a world cluttered with a variety of obstacles by introducing a new distributed algorithm for reconfiguring the formation shape. We systematically validate the reconfiguration algorithm using three real robots in scenarios of increasing complexity.

关键词： Navigation Robot kinematics Collision avoidance Shape Robot sensing systems Laplace equations

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A distributed noise-resistant Particle Swarm Optimization algorithm for high-dimensional multi-robot learning

A distributed noise-resistant Particle Swarm Optimization al...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Ezequiel Di Mario Iñaki Navarro Alcherio Martinoli Distributed Intelligent Systems and Algorithms Laboratory School of Architecture Civil and Environmental Engineering

ISBN: (纸本)9781479969241

Population-based learning techniques have been proven to be effective in dealing with noise in numerical benchmark functions and are thus promising tools for the high-dimensional optimization of controllers for multiple robots with limited sensing capabilities, which have inherently noisy performance evaluations. In this article, we apply a statistical technique called Optimal Computing Budget Allocation to improve the performance of Particle Swarm Optimization in the presence of noise for a multi-robot obstacle avoidance benchmark task. We present a new distributed PSO OCBA algorithm suitable for resource-constrained mobile robots due to its low requirements in terms of memory and limited local communication. Our results from simulation show that PSO OCBA outperforms other techniques for dealing with noise, achieving a more consistent progress and a better estimate of the ground-truth performance of candidate solutions. We then validate our simulations with real robot experiments where we compare the controller learned with our proposed algorithm to a potential field controller for obstacle avoidance in a cluttered environment. We show that they both achieve a high performance through different avoidance behaviors.

关键词： Robot sensing systems Noise Collision avoidance Benchmark testing Resource management Mobile robots

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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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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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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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