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IEEE International Conference on Robotics and Automation (ICRA)

作者： William C. Evans Grégory Mermoud Alcherio Martinoli Distributed Intelligent Systems and Algorithms Laboratory École Polytechnique Fédérale Lausanne Vaud Switzerland

We propose two contrasting approaches to the scalable distributed control of a swarm of self-assembling miniaturized robots, specifically the formation of chains of a desired length: (1) a deterministic controller in which robots communicate with each other in order to directly limit the size of each chain, and (2) a probabilistic controller where the average chain size is controlled by the probability a robot will choose to leave its chain. We demonstrate the feasibility of both approaches by implementing them on a real swarm of Alice robots. Using Webots, a realistic simulator for mobile robotics, and macroscopic models based on the Chemical Reaction Network (CRN) framework, we investigate the limitations of the deterministic controller and demonstrate the existence of optimal parameters for the probabilistic controller where exploration and exploitation are well balanced, thus favoring the formation of larger chains.

关键词： distributed control Robot kinematics Robot sensing systems Self-assembly Mobile robots Size control Aggregates Robotics and automation Optimal control Context modeling

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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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A realistic simulator for the design and evaluation of intelligent vehicles

A realistic simulator for the design and evaluation of intel...

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International Conference on intelligent Transportation

作者： Sven Gowal Yizhen Zhang Alcherio Martinoli Distributed Intelligent Systems and Algorithms Laboratory Ecole Polytechnique Fédérale de Lausanne Switzerland Applied Materials Inc. Santa Clara CA USA

The number of vehicles hitting the road each day is rapidly increasing, and several problems, such as traffic congestion or driver safety, can no longer be solved in the same fashion as before. intelligent transportation systems could potentially solve part of these problems, but prototyping, designing and testing cooperative smart vehicles is a cumbersome task. This paper presents a realistic simulator, capable of operating both at microscopic and sub-microscopic level, where intelligent vehicles can be designed and analyzed with a pragmatic approach. A number of advances in robotics have already been transferred to vehicular technology, with a potential increase of this trend into the future. Here, we develop a plugin for a well-established robotics simulator (Webots), in order to reinforce at the virtual level this cross-fertilization between the two areas and create a baseline for realistic studies of future solutions in real intelligent vehicles.

关键词： Vehicles Sensors intelligent vehicles Biological system modeling Vehicle dynamics Wheels Engines

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Local graph-based distributed control for safe highway platooning

Local graph-based distributed control for safe highway plato...

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2010 IEEE/RSJ International Conference on intelligent Robots and systems

作者： Sven Gowal Riccardo Falconi Alcherio Martinoli Distributed Intelligent Systems and Algorithms Laboratory Ecole Polytechnique Fédérale de Lausanne Switzerland Dipartimento di Elettronica Informatica e Sistemistica Università di Bologna Italy

Using graph theory, this paper investigates how a group of vehicles, endowed with local positioning capabilities (range and bearing to other vehicles), can keep a predefined formation. We propose a longitudinal and lateral controller that stabilizes a system of several vehicles as well as a collision avoidance mechanism. The stability of our approach is supported by a mathematical analysis as well as realistic simulations.

关键词： Vehicles Laplace equations Equations Feedback control Trajectory Graph theory Stability analysis

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distributed scalable multi-robot learning using particle swarm optimization

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Swarm Intelligence 2009年第3期3卷 203-222页

作者： Pugh, Jim Martinoli, Alcherio Distributed Intelligent Systems Algorithms Group École Polytechnique Fédérale de Lausanne 1015 Lausanne Switzerland

Designing effective behavioral controllers for mobile robots can be difficult and tedious;this process can be circumvented by using online learning techniques which allow robots to generate their own controllers online in an automated fashion. In multi-robot systems, robots operating in parallel can potentially learn at a much faster rate by sharing information amongst themselves. In this work, we use an adapted version of the Particle Swarm Optimization algorithm in order to accomplish distributed online robotic learning in groups of robots with access to only local information. The effectiveness of the learning technique on a benchmark task (generating high-performance obstacle avoidance behavior) is evaluated for robot groups of various sizes, with the maximum group size allowing each robot to individually contain and manage a single PSO particle. To increase the realism of the technique, different PSO neighborhoods based on limitations of real robotic communication are tested and compared in this scenario. We explore the effect of varying communication power for one of these communication-based PSO neighborhoods. To validate the effectiveness of these learning techniques, fully distributed online learning experiments are run using a group of 10 real robots, generating results which support the findings from our simulations. © Springer Science + Business Media, LLC 2009.

关键词： Multipurpose robots

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Graph-based distributed control for non-holonomic vehicles engaged in a reconfiguration task using local positioning information

Graph-based distributed control for non-holonomic vehicles e...

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2009 2nd International Conference on Robot Communication and Coordination, RoboComm 2009

作者： Falconi, Riccardo Gowal, Sven Pugh, Jim Martinoli, Alcheri Dipartimento di Elettronica Informatica e Sistemistica of the Universita di Bologna Italy Distributed Intelligent Systems Algorithms Laboratory of the Ecole Polytechnique Fédérale de Lausanne Switzerland

ISBN: (纸本)9789639799516

Formation building and keeping among vehicles has been studied for many years, since 1987 with Reynolds' rules [1]. This paper presents a control algorithm, based on recent work in graph theory, able to reconfigure static formations of non-holonomic vehicles endowed solely with local positioning capabilities. The convergence of our approach is mathematically proven and applied to a realistic robotic platform.

关键词： Graph theory

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Localizing an Odor Source and Avoiding Obstacles: Experiments in a Wind Tunnel using Real Robots

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AIP Conference Proceedings 2009年第1期1137卷 69-72页

作者： Thomas Lochmatter Nicolas Heiniger Alcherio Martinoli Ecole Polytechnique Fédérate de Lausanne (EPFL) Distributed Intelligent Systems and Algorithms Laboratory (DISAL)

We report on real‐robot odor source localization experiments carried out in an environment with obstacles in the odor plume. The robot was equipped with an ethanol sensor and a wind direction sensor, and the experiments were carried out in a wind tunnel (controlled environment). An enhanced version of the surge‐spiral algorithm was used, which was augmented with a dedicate behavior to manage obstacles (avoid them, or follow their contour). We compare the results in terms of distance overhead and success rate, and discuss the impact of obstacles on plume traversal.

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Graph-based distributed control for non-holonomic vehicles engaged in a reconfiguration task using local positioning information

Graph-based distributed control for non-holonomic vehicles e...

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International Conference on Robot Communication and Coordination, ROBOCOMM

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

关键词： distributed control Vehicles Robot kinematics Mobile robots Graph theory Steady-state Multiagent systems Laplace equations intelligent robots Convergence

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Towards Multi-Level Modeling of Self-Assembling intelligent Micro-systems 09

Towards Multi-Level Modeling of Self-Assembling Intelligent ...

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International Conference on Autonomous Agents and Multiagent systems

作者： Gregory Mermoud Juergen Brugger Alcherio Martinoli Distributed Intelligent Systems and Algorithms Laboratory EPFL-ENAC-ISTE-DISAL Ecole Polytechnique Federale de Lausanne (EPFL) Microsystems Laboratory EPFL-STI-IMT-LMIS Ecole Polytechnique Federale de Lausanne (EPFL)

ISBN: (纸本)9781615673346

We investigate and model the dynamics of two-dimensional stochastic self-assembly of intelligent micro-systems with minimal requirements in terms of sensing, actuation, and control. A microscopic agent-based model accounts for spatiality and serves as a baseline for assessing the accuracy of models at higher abstraction level. Spatiality is relaxed in Monte Carlo simulations, which still capture the binding energy of each individual aggregate. Finally, we introduce a macroscopic model that only keeps track of the average number of aggregates in each energy state. This model is able to quantitatively and qualitatively predict the dynamics observed at lower, more detailed modeling levels. Since we investigate an idealized system, thus making very few assumptions about the exact nature of the final target system, our framework is potentially applicable to a large body of self-assembling agents ranging from functional micro.-robots endowed with simple sensors and actuators to elementary microfabricated parts. In particular, we show how our suite of models at different abstraction levels can be used for optimizing both the design of the building blocks and the control of the stochastic process.

关键词： Theory Performance Design Aggregation Self-assembly Micro-robotics Monte Carlo simulations Macroscopic modeling Multi-level modeling Monte Carlo technique hierarchical models Abstraction Markov chain theories Macroscopic models Self-assembly aggregates agglomeration

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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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