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Modelling a wireless connected swarm of mobile robots

Swarm Intelligence 2008年第2-4期2卷 241-266页

作者： Winfield, Alan F.T. Liu, Wenguo Nembrini, Julien Martinoli, Alcherio Bristol Robotics Laboratory University of the West of England Coldharbour Lane Bristol BS16 1QY United Kingdom Distributed Intelligent Systems and Algorithms Laboratory École Polytechnique Fédérale de Lausanne 1015 Lausanne Switzerland

It is a characteristic of swarm robotics that modelling the overall swarm behaviour in terms of the low-level behaviours of individual robots is very difficult. Yet if swarm robotics is to make the transition from the laboratory to real-world engineering realisation such models would be critical for both overall validation of algorithm correctness and detailed parameter optimisation. We seek models with predictive power: models that allow us to determine the effect of modifying parameters in individual robots on the overall swarm behaviour. This paper presents results from a study to apply the probabilistic modelling approach to a class of wireless connected swarms operating in unbounded environments. The paper proposes a probabilistic finite state machine (PFSM) that describes the network connectivity and overall macroscopic behaviour of the swarm, then develops a novel robot-centric approach to the estimation of the state transition probabilities within the PFSM. Using measured data from simulation the paper then carefully validates the PFSM model step by step, allowing us to assess the accuracy and hence the utility of the model. © Springer Science + Business Media, LLC 2008.

关键词： Robots

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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 IEEE Conference on intelligent Transportation systems

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

ISBN: (纸本)9781424476572

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. ©2010 IEEE.

关键词： intelligent vehicle highway systems

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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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Analysis of fitness noise in particle swarm optimization: From robotic learning to benchmark functions

Analysis of fitness noise in particle swarm optimization: Fr...

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Congress on Evolutionary Computation

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

ISBN: (纸本)9781479914869

Population-based learning techniques have been proven to be effective in dealing with noise and are thus promising tools for the optimization of robotic controllers, which have inherently noisy performance evaluations. This article discusses how the results and guidelines derived from tests on benchmark functions can be extended to the fitness distributions encountered in robotic learning. We show that the large-amplitude noise found in robotic evaluations is disruptive to the initial phases of the learning process of PSO. Under these conditions, neither increasing the population size nor increasing the number of iterations are efficient strategies to improve the performance of the learning. We also show that PSO is more sensitive to good spurious evaluations of bad solutions than bad evaluations of good solutions, i.e., there is a non-symmetric effect of noise on the performance of the learning.

关键词： Benchmark testing Noise Standards Optimization Robot sensing systems Noise measurement

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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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The role of environmental and controller complexity in the distributed optimization of multi-robot obstacle avoidance

The role of environmental and controller complexity in the d...

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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

The ability to move in complex environments is a fundamental requirement for robots to be a part of our daily lives. Increasing the controller complexity may be a desirable choice in order to obtain an improved performance. However, these two aspects may pose a considerable challenge on the optimization of robotic controllers. In this paper, we study the trade-offs between the complexity of reactive controllers and the complexity of the environment in the optimization of multi-robot obstacle avoidance for resource-constrained platforms. The optimization is carried out in simulation using a distributed, noise-resistant implementation of Particle Swarm Optimization, and the resulting controllers are evaluated both in simulation and with real robots. We show that in a simple environment, linear controllers with only two parameters perform similarly to more complex non-linear controllers with up to twenty parameters, even though the latter ones require more evaluation time to be learned. In a more complicated environment, we show that there is an increase in performance when the controllers can differentiate between front and backwards sensors, but increasing further the number of sensors and adding non-linear activation functions provide no further benefit. In both environments, augmenting reactive control laws with simple memory capabilities causes the highest increase in performance. We also show that in the complex environment the performance measurements are noisier, the optimal parameter region is smaller, and more iterations are required for the optimization process to converge.

关键词： Optimization Complexity theory Robot sensing systems Mobile robots Wheels

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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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Towards optimally efficient field estimation with threshold-based pruning in real robotic sensor networks

Towards optimally efficient field estimation with threshold-...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Amanda Prorok Christopher M. Cianci Alcherio Martinoli Distributed Intelligent Systems and Algorithms Laboratory Ecole Polytechnique Federale de Lausanne Switzerland

The efficiency of distributed sensor networks depends on an optimal trade-off between the usage of resources and data quality. The work in this paper addresses the problem of optimizing this trade-off in a self-configured distributed robotic sensor network, with respect to a user-defined objective function. We investigate a quadtree network topology and implement a fully distributed threshold-based field estimation algorithm. Simulations with field data as well as real robot experiments are performed, validating our distributed control strategy and evaluating the threshold-based formula for real world scenarios. We propose a theoretical analysis that predicts the system's behavior in real world case studies. The experiments and this prediction show very good correspondence, enabling the accurate employment of the objective function, optimizing the trade-off based on user needs.

关键词： Robot sensing systems Routing Sensor phenomena and characterization Wireless sensor networks Signal processing algorithms Monitoring Robotics and automation Network topology Space technology Clustering algorithms

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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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Swarm robotic plume tracking for intermittent and time-variant odor dispersion

Swarm robotic plume tracking for intermittent and time-varia...

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European Conference on Mobile Robots (ECMR)

作者： Ali Marjovi Lino Marques EPFL Distributed Intelligent Systems and Algorithms Laboratory Switzerland Institute of Systems and Robotics University of Coimbra Portugal

This paper presents a method for odor plume tracking by a swarm of robots in realistic conditions. In real world environments, the chemical concentration within an odor plume is patchy, intermittent and time-variant. This study shows that swarm robots can cooperatively track the odor plume towards its source by establishing a cohesive spatial sensor network to deal with the turbulences and patchy nature of odor plumes. The robots move together and maintain a distance margin between themselves in order to keep the cohesion of the constructed sensor network while the odor concentration and air-flow speed are considered in the equations of navigation of the robots in the network to more efficiently track the plume. The method is evaluated in simulation against various number of robots, the emission rate of the odor source, the number of obstacles in the environment and the size of the testing environment. The emergent behavior of the swarm proves the functionality, robustness and scalability of the system in different conditions.

关键词： Robot sensing systems Equations Mathematical model Force Olfactory Testing

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