The marXbot, a miniature mobile robot opening new perspectives for the collective-robotic research

Bonani, Michaël; Longchamp, Valentin; Magnenat, Stéphane; Rétornaz, Philippe; Burnier, Daniel; Roulet, Gilles; Vaussard, Florian; Bleuler, Hannes; Mondada, Francesco

doi:10.1109/iros.2010.5649153

Cited by 163 publications

(138 citation statements)

References 11 publications

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“…The task is to collectively transport the object from an initial to a goal location. The robots we used are modeled after the foot-bot robot [15], developed within the Swarmanoid project 1 . The irregularly shaped object is an object which cannot be grasped through its entire perimeter but only in certain regions.…”

Section: Task Definitionmentioning

confidence: 99%

Socially-Mediated Negotiation for Obstacle Avoidance in Collective Transport

Ferrante

Brambilla

Birattari

et al. 2013

Springer Tracts in Advanced Robotics

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Abstract. In this paper, we present a novel method for performing collective transport in the presence of obstacles. Three robots are physically connected to an object to be transported from a start to a goal location. The task is particularly challenging because the robots have a heterogeneous perception of the environment. In fact, the goal and the obstacles can be perceived only by some of the robots. Hence, the task requires appropriate negotiation of the direction among the robots. We developed a novel negotiation strategy in order to tackle this challenge. We perform experiments in simulation.In the experiments, we analyze efficiency in an environment with only one obstacle, and robustness in an environment with several obstacles.

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Section: Task Definitionmentioning

confidence: 99%

Socially-Mediated Negotiation for Obstacle Avoidance in Collective Transport

Ferrante

Brambilla

Birattari

et al. 2013

Springer Tracts in Advanced Robotics

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“…The simulated MarXbots (Bonani et al 2010) are circular robots with a radius of 8.5 cm. 2 Each experiment is performed with three types of homogeneous robot swarms that represent three different robot control strategies commonly used in the swarm robotics literature and used here to highlight the ICR framework.…”

Section: Robots and Robot Control Strategiesmentioning

confidence: 99%

The Information-Cost-Reward framework for understanding robot swarm foraging

2017

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Demand for autonomous swarms, where robots can cooperate with each other without human intervention, is set to grow rapidly in the near future. Currently, one of the main challenges in swarm robotics is understanding how the behaviour of individual robots leads to an observed emergent collective performance. In this paper, a novel approach to understanding robot swarms that perform foraging is proposed in the form of the InformationCost-Reward (ICR) framework. The framework relates the way in which robots obtain and share information (about where work needs to be done) to the swarm's ability to exploit that information in order to obtain reward efficiently in the context of a particular task and environment. The ICR framework can be applied to analyse underlying mechanisms that lead to observed swarm performance, as well as to inform hypotheses about the suitability of a particular robot control strategy for new swarm missions. Additionally, the informationcentred understanding that the framework offers paves a way towards a new swarm design methodology where general principles of collective robot behaviour guide algorithm design.

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“…We employ a marXbot [20], a miniature, modular, all-terrain experimentation robot developed within the Swarmanoid project [21]. Fig.…”

Section: Autonomous Robot: Marxbotmentioning

confidence: 99%

Autonomous Construction with Compliant Building Material

Soleymani

Trianni

Bonani

et al. 2015

Intelligent Autonomous Systems 13

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Abstract. In this paper, we develop an autonomous construction system in which a self-contained ground robot builds a protective barrier by means of compliant pockets (i.e., filled bags). We present a stochastic control algorithm based on two biological mechanisms (stigmergy and templates) that takes advantage of compliant pockets for autonomous construction. The control algorithm guides the robot to build the structure without relying on any external motion capture system or external computer. We propose a statistical model to represent the structures built with the compliant pockets, and we provide a set of criteria for assessing the performance of the proposed system. To demonstrate the feasibility of the proposed system, real-robot experiments were carried out. In each experiment, the robot successfully built the structure. The results show the viability of the proposed autonomous construction system.

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The marXbot, a miniature mobile robot opening new perspectives for the collective-robotic research

Cited by 163 publications

References 11 publications

Socially-Mediated Negotiation for Obstacle Avoidance in Collective Transport

Socially-Mediated Negotiation for Obstacle Avoidance in Collective Transport

The Information-Cost-Reward framework for understanding robot swarm foraging

Autonomous Construction with Compliant Building Material

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