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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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A comparison of PSO and Reinforcement Learning for multi-robot obstacle avoidance

A comparison of PSO and Reinforcement Learning for multi-rob...

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Congress on Evolutionary Computation

作者： Ezequiel Di Mario Zeynab Talebpour Alcherio Martinoli Distributed Intelligent Systems and Algorithms Laboratory Ecole Polytechnique Fédérale de Lausanne Switzerland

ISBN: (纸本)9781479904532

The design of high-performing robotic controllers constitutes an example of expensive optimization in uncertain environments due to the often large parameter space and noisy performance metrics. There are several evaluative techniques that can be employed for on-line controller design. Adequate benchmarks help in the choice of the right algorithm in terms of final performance and evaluation time. In this paper, we use multi-robot obstacle avoidance as a benchmark to compare two different evaluative learning techniques: Particle Swarm Optimization and Q-learning. For Q-learning, we implement two different approaches: one with discrete states and discrete actions, and another one with discrete actions but a continuous state space. We show that continuous PSO has the highest fitness overall, and Q-learning with continuous states performs significantly better than Q-learning with discrete states. We also show that in the single robot case, PSO and Q-learning with discrete states require a similar amount of total learning time to converge, while the time required with Q-learning with continuous states is significantly larger. In the multi-robot case, both Q-learning approaches require a similar amount of time as in the single robot case, but the time required by PSO can be significantly reduced due to the distributed nature of the algorithm.

关键词： Robot sensing systems Mobile robots Collision avoidance Wheels Optimization

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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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An Experimental Study in Wireless Connectivity Maintenance Using up to 40 Robots Coordinated by an Institutional Robotics Approach

An Experimental Study in Wireless Connectivity Maintenance U...

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IEEE/RSJ International Conference on intelligent Robots and systems

作者： Jose N. Pereira Porfirio Silva Pedro U. Lima Alcherio Martinoli Distributed Intelligent Systems and Algorithms Laboratory EPFL Lausanne Switzerland Institute for Systems and Robotics Instituto Superior Técnico Lisbon Portugal

ISBN: (纸本)9781467363563

This work is developed in the framework of Institutional Robotics (IR), an approach to cooperative distributed robotic systems that draws inspiration from the social sciences. We consider a case study concerned with a swarm of simple robots which has to maintain wireless connectivity and a certain degree of spatial compactness. Robots have local, bounded communication capabilities and have to execute the task (running an IR controller) using exclusively as information their current number of wireless connections to neighbors. For the very same case study, we previously introduced an IR-based macroscopic model for the behavior of a large number of robots, validated using a submicroscopic model implemented through a realistic simulator. In this work, we go a step further and validate our submicroscopic model with real world experiments, duplicating accurately the conditions used, including a large number of robots and noisy communication channels. The main conclusions of this paper are two-fold. First, the IR approach was able to maintain the wireless connectivity of a swarm of 40 real, resource-constrained robots. This speaks in favor of the robustness and scalability of such approach. Second, the submicroscopic model implemented is faithfully capturing the reality and can be used to further optimize the performances of distributed control strategies using an IR approach.

关键词： IR reality can be used Wireless connectivity Robot Reality iridium dike swarms robotics role model

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Multi-Robot Coordination in Dynamic Environments Shared with Humans

Multi-Robot Coordination in Dynamic Environments Shared with...

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IEEE International Conference on Robotics and Automation

作者： Zeynab Talebpour Alcherio Martinoli Distributed Intelligent Systems and Algorithms Laboratory (DISAL) Ecole Polytechnique Federale de Lausanne (EPFL) Lausanne Switzerland

This work addresses multi-robot coordination in social human-populated environments using a market-based framework for solving the Multi-Robot Task Allocation (MRTA) problem. Humans are considered in the proposed coordination mechanism by means of accounting for social costs in bid evaluations and requesting collaboration in socially blocking situations. Initially, the effect of a realistic environment with varying number of static/moving humans on the behavior and performance of our method is studied through an extensive suite of experiments in a high-fidelity simulator. Results show that the total traveled distance and time are increased when humans are present in the environments. Localization noise is also increased particularly in the case of static people. In the second series of experiments, a number of problematic cases resulting in longer modified paths, blocked passages, and long waits have been investigated. A comparative study targeting human-agnostic navigation and planning, human-aware navigation and human-agnostic planning, and human-aware navigation and planning has been conducted. Both simulated and real robot experiments confirm the effectiveness of accounting for humans at both team and individual levels. This leads to respecting social constraints as well as achieving a better performance based on MRTA metrics.

关键词： Robot kinematics Task analysis Navigation Planning Resource management Measurement

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Adaptive Lévy Taxis for odor source localization in realistic environmental conditions

Adaptive Lévy Taxis for odor source localization in realist...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Romain Emery Faezeh Rahbar Ali Marjovi Alcherio Martinoli Intelligent Systems and Algorithms Laboratory Ecole Polytechnique Fédérale de Lausanne (EPFL) Lausanne Switzerland

Odor source localization with mobile robots has recently been subject to many research works, but remains a challenging task mainly due to the large number of environmental parameters that make it hard to describe gas concentration fields. We designed a new algorithm called Adaptive Lévy Taxis (ALT) to achieve odor plume tracking through a correlated random walk. In order to compare its performances with well-established solutions, we have implemented three moth-inspired algorithms on the same robotic platform. To improve the performance of the latter algorithms, we developed a rigorous way to determine one of their key parameters, the odor concentration threshold at which the robot considers to be inside or outside the plume. The methods have been systematically evaluated in a large wind tunnel under various environmental conditions. Experiments revealed that the performance of ALT is consistently good in all environmental conditions (in particular when compared to the three reference algorithms) in terms of both distance traveled to find the source and success rate.

关键词： Robots Public transportation Algorithm design and analysis Hidden Markov models Probability distribution Complexity theory Classification algorithms

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An overtaking decision algorithm for networked intelligent vehicles based on cooperative perception

An overtaking decision algorithm for networked intelligent v...

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IEEE Symposium on intelligent Vehicle

作者： Milos Vasic Gael Lederrey Iñaki Navarro Alcherio Martinoli The Distributed Intelligent Systems and Algorithms Laboratory Ecole Polytechnique Fédérale de Lausanne (EPFL) Switzerland

ISBN: (纸本)9781509018222

This paper presents an overtaking decision algorithm for networked intelligent vehicles. The algorithm is based on a cooperative tracking and sensor fusion algorithm that we previously developed. The ego vehicle is equipped with lane keeping and lane changing capabilities, as well as a forward-looking lidar sensor. The lidar data are fed to the tracking module which detects other vehicles, such as the vehicle that is to be overtaken (leading) and the oncoming traffic. Based on the estimated distances to the leading and the oncoming vehicles and their speeds, a risk is calculated and a corresponding overtaking decision is made. We compare the performance of the overtaking algorithm between the case when the ego vehicle only relies on its lidar sensor, and the case in which it fuses object estimates received from the leading car which also has a forward-looking lidar. Systematic evaluations are performed in Webots, a calibrated high-fidelity simulator.

关键词： Automobiles Target tracking Laser radar intelligent vehicles Clustering algorithms Fuses

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Assembly of configurations in a networked robotic system: A case study on a reconfigurable interactive table lamp

Assembly of configurations in a networked robotic system: A ...

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IEEE Swarm Intelligence Symposium, SIS

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

In the present study, we are interested in verifying how the progressive addition of constraints on communication and localization impact the performance of a swarm of small robots in shape formation tasks. Identified to be of importance in a swarm-user interaction context, the time required to construct a given spatial configuration is considered as a performance metric. The experimental work reported in this paper starts from global and synchronized localization information, shown to be successful both on a real hardware system and in simulation. In a second step, communication is constrained to a local scale, thus obliging a single designated robot to disseminate the global localization information to the other agents. The reliability of the radio communication channel and its impact upon the performance of the system are considered.

关键词： Robotic assembly Assembly systems Lamps Robot kinematics Mobile robots intelligent robots Humans Shape Multirobot systems System testing

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Hard Problems are Easier for Success-based Parameter Control

arXiv

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arXiv 2022年

作者： Fajardo, Mario Alejandro Hevia Sudholt, Dirk Department of Computer Science University of Sheffield Sheffield United Kingdom Algorithms for Intelligent Systems University of Passau Passau Germany

Recent works showed that simple success-based rules for selfadjusting parameters in evolutionary algorithms (EAs) can match or outperform the best fixed parameters on discrete problems. Nonelitism in a (1, λ) EA combined with a self-adjusting offspring population size λ outperforms common EAs on the multimodal Cliff problem. However, it was shown that this only holds if the success rate s that governs self-adjustment is small enough. Otherwise, even on OneMax, the self-adjusting (1, λ) EA stagnates on an easy slope, where frequent successes drive down the offspring population size. We show that self-adjustment works as intended in the absence of easy slopes. We define everywhere hard functions, for which successes are never easy to find and show that the self-adjusting (1, λ) EA is robust with respect to the choice of success rates s. We give a general fitness-level upper bound on the number of evaluations and show that the expected number of generations is at most O(d + log(1/pmin+)) where d is the number of non-optimal fitness values and pmin+is the smallest probability of finding an improvement from a non-optimal search point. We discuss implications for the everywhere hard function LeadingOnes and a new class OneMaxBlocks of everywhere hard functions with tunable difficulty. Copyright © 2022, The Authors. All rights reserved.

关键词： Population statistics

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A Distributed Source Term Estimation Algorithm for Multi-Robot systems

A Distributed Source Term Estimation Algorithm for Multi-Rob...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Faezeh Rahbar Alcherio Martinoli Distributed Intelligent Systems and Algorithms Laboratory École Polytechnique Fédérale de Lausanne (EPFL) Lausanne Switzerland

ISBN: (数字)9781728173955

ISBN: (纸本)9781728173962

Finding sources of airborne chemicals with mobile sensing systems finds applications in safety, security, and emergency situations related to medical, domestic, and environmental domains. Given the often critical nature of all the applications, it is important to reduce the amount of time necessary to accomplish this task through intelligent systems and algorithms. In this paper, we extend a previously presented algorithm based on source term estimation for odor source localization for homogeneous multi-robot systems. By gradually increasing the level of coordination among multiple mobile robots, we study the benefits of a distributed system on reducing the amount of time and resources necessary to achieve the task at hand. The method has been evaluated systematically through high-fidelity simulations and in a wind tunnel emulating realistic and repeatable conditions in different coordination scenarios and with different number of robots.

关键词： Robot kinematics Robot sensing systems Estimation Navigation Probabilistic logic

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