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International Conference on Indoor Positioning and Indoor Navigation (IPIN)

作者： Amanda Prorok Phillip Tomé Alcherio Martinoli Distributed Intelligent Systems and Algorithms Laboratory School of Architecture Civil and Environmental Engineering Ecole Polytechnique Fédérale de Lausanne Switzerland Electronics and Signal Processing Laboratory School of Engineering Ecole Polytechnique Fédérale de Lausanne Switzerland

Ultra-wideband (UWB) localization is one of the most promising indoor localization methods. Yet, non-line-of-sight (NLOS) positioning scenarios can potentially cause significant localization errors and remain a challenge. In this work, we propose a novel, probabilistic UWB TDOA error model which explicitly takes into account NLOS. In order to validate our approach systematically in a real world setup, we leverage the utility of a group of mobile robots, and introduce our error model into a real-time localization framework run onboard the robots. We subsequently extend our framework by employing a collaborative localization strategy which enables the sharing of inter-robot, relative position observations. Our experimental results show how the novel TDOA error model is able to improve localization performance when information on the LOS/NLOS path condition is available. These results are complemented by additional experiments which show how a collaborative team of robots is able to significantly improve localization performance when no information on the LOS/NLOS path condition is available.

关键词： Robot kinematics Mathematical model Robot sensing systems Measurement uncertainty Atmospheric measurements Particle measurements

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SwisTrack - A Flexible Open Source Tracking Software for Multi-Agent systems

SwisTrack - A Flexible Open Source Tracking Software for Mul...

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2008 IEEE/RSJ International Conference on intelligent Robots and systems, Pages 3661-4172

作者： Thomas Lochmatter Pierre Roduit Chris Cianci Nikolaus Correll Jacques Jacot Alcherio Martinoli Distributed Intelligent Systems and Algorithms Laboratory Ecole Polytechnique Federale de Lausanne 1015 Lausanne Switzerland

ISBN: (纸本)9781424420575

Vision-based tracking is used in nearly all robotic laboratories for monitoring and extracting of agent positions, orientations, and trajectories. However, there is currently no accepted standard software solution available, so many research groups resort to developing and using their own custom software. In this paper, we present Version 4 of SwisTrack, an open source project for simultaneous tracking of multiple agents. While its broad range of pre-implemented algorithmic components allows it to be used in a variety of experimental applications, its novelty stands in its highly modular architecture. Advanced users can therefore also implement additional customized modules which extend the functionality of the existing components within the provided interface. This paper introduces SwisTrack and shows experiments with both marked and marker-less agents.

关键词： Multi-agent systems open source Custom software Agents Resorts tracking standard software

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Specialization as an optimal strategy under varying external conditions

Specialization as an optimal strategy under varying external...

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2009 IEEE International Conference on Robotics and Automation, ICRA '09

作者： Hsieh, M. Ani Halász, Ádám Cubuk, Ekin Dogus Schoenholz, Samuel Martinoli, Alcherio Mechanical Engineering and Mechanics Department Drexel University 3141 Chestnut Street Philadelphia PA 19104 United States Department of Mathematics West Virginia University P.O. Box 6310 Morgantown WV 26506 United States Swarthmore College 500 College Ave. Swarthmore PA 19081 United States Distributed Intelligent Systems and Algorithms Laboratory École Politechnique Fédérale de Lausanne CH-1015 Lausanne Switzerland

ISBN: (纸本)9781424427895

We present an investigation of specialization when considering the execution of collaborative tasks by a robot swarm. Specifically, we consider the stick-pulling problem first proposed by Martinoli et al. [1], [2] and develop a macroscopic analytical model for the swarm executing a set of tasks that require the collaboration of two robots. We show, for constant external conditions, maximum productivity can be achieved by a single species swarm with carefully chosen operational parameters. While the same applies for a two species swarm, we show how specialization is a strategy best employed for changing external conditions.© 2009 IEEE.

关键词： Swarm intelligence

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Optimal path planning and coverage control for multi-robot persistent coverage in environments with obstacles

Optimal path planning and coverage control for multi-robot p...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： José Manuel Palacios-Gasós Zeynab Talebpour Eduardo Montijano Carlos Sagüés Alcherio Martinoli Instituto de Investigación en Ingeniería de Aragón (I3A) Universidad de Zaragoza Zaragoza Spain Ecole Polytechnique Fédrale de Lausanne Zeynab Talebpour and Alcherio Martinoli are with Distributed Intelligent Systems and Algorithms Laboratory Lausanne Switzerland

Persistent coverage aims to maintain a certain coverage level over time in an environment where such level deteriorates. This level can be associated to temperature, dust or sensor information. We propose an algorithmic solution in which each robot locally finds the best paths and coverage actions to keep the desired coverage level over the whole environment. Using Fast Marching Methods, optimal paths are computed in terms of coverage quality, while keeping a safety distance to obstacles. Additionally, our solution enables a computationally efficient evaluation of a list of potential trajectories, allowing us to choose the one that mostly improves the coverage along the whole path. The combination of this algorithm with a Dynamic Window navigation makes our approach competitive in terms of flexibility and robustness in changing environments with existing solutions. Finally, we also propose a coverage action controller, locally computed and optimal, that makes the robots maintain the coverage level of the environment significantly close to the objective. Simulations and real experiments validate the whole approach.

关键词： Robot sensing systems Planning Trajectory Collision avoidance Production

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Evolutionary multi-criterion optimization

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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2003年 2632卷

作者： Fonseca, Carlos M. Fleming, Peter J. Zitzler, Eckart Deb, Kalyanmoy Thiele, Lothar University of the Algarve Centre for Intelligent Systems Campus de Gambelas Faro Portugal University of Sheffield Department of Automatic Control and Systems Engineering Mappin Street Sheffield United Kingdom Swiss Federal Institute of Technology Department of Electrical Engineering Computer Engineering and Networks Laboratory Gloriastrabe 35 Zurich Switzerland Indian Institute of Technology Department of Mechanical Engineering Kanpur Genetic Algorithms Laboratory Kanpur India

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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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Flexible triangular formation keeping of marine robotic vehicles using range measurements 1

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IFAC Proceedings Volumes 2014年第3期47卷 5145-5150页

作者： Francisco Rego Jorge M. Soares António Pascoal A. Pedro Aguiar Colin Jones Laboratory of Robotics and Systems in Engineering and Science Instituto Superior Técnico University of Lisbon Lisbon Portugal Department of Electrical and Computer Engineering Faculty of Engineering University of Porto Porto Portugal Institute of Mechanical Engineering School of Engineering École Polytechnique Fédérale de Lausanne Lausanne Switzerland Distributed Intelligent Systems and Algorithms Laboratory School of Architecture Civil and Environmental Engineering École Polytechnique Fédérale de Lausanne Lausanne Switzerland National Institute of Oceanography Dona Paula Goa India

This paper addresses the problem of keeping an autonomous marine vehicle in a moving triangular formation by regulating its position with respect to two leader vehicles. The follower vehicle has no prior knowledge of the path described by the leaders but has access to their heading angle and is able to measure inter-vehicle ranges. It is assumed that the distance between the leaders is constant and known. A control strategy is adopted that generates speed and heading commands so as to drive suitably defined along track and cross track errors to zero. The commands are used as input to local inner loops for yaw and speed control. The paper describes the algorithms derived for range-based control and assesses their performance in simulations using realistic models of the vehicles involved. Tests with three autonomous marine vehicles equipped with acoustic modems and ranging devices allow for the evaluation of the performance of the algorithms in a real-world situation.

关键词： Autonomous Vehicles Marine systems Control Laws Formation Control Station Keeping Triangular Formations

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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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Specialization as an optimal strategy under varying external conditions

Specialization as an optimal strategy under varying external...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： M. Ani Hsieh Adam Halasz Ekin Dogus Cubuk Samuel Schoenholz Alcherio Martinoli Mechanical Engineering and Mechanics Department Drexel University Philadelphia PA USA Department of Mathematics West Virginia University Morgantown WV USA Swarthmore College Swarthmore PA USA Distributed Intelligent Systems and Algorithms Laboratory École Polytechnique Fédérale de Lausanne Lausanne Switzerland

We present an investigation of specialization when considering the execution of collaborative tasks by a robot swarm. Specifically, we consider the stick-pulling problem first proposed by Martinoli et al., and develop a macroscopic analytical model for the swarm executing a set of tasks that require the collaboration of two robots. We show, for constant external conditions, maximum productivity can be achieved by a single species swarm with carefully chosen operational parameters. While the same applies for a two species swarm, we show how specialization is a strategy best employed for changing external conditions.

关键词： Educational robots Robot kinematics Collaboration Robot sensing systems Analytical models Productivity Environmental economics Microorganisms Educational institutions Robotics and automation

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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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