Hybrid Control for a Real Swarm Robotics System in an Intruder Detection Task

Duarte, Miguel; Gomes, Jorge; Costa, Vasco; Oliveira, Sancho; Christensen, Anders Lyhne

doi:10.1007/978-3-319-31153-1_15

Cited by 15 publications

(12 citation statements)

References 27 publications

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“…In both of the two studies discussed above, the performance and behavior observed on the real robots was similar to those observed in simulation [4], [14]. In this way, the hardware platform presented in this paper has facilitated novel contributions to the field of swarm robotics, and most notably, was used in the first successful demonstration of evolved control outside of strictly controlled laboratory conditions [3], [4].…”

Section: Studies Conducted With the Platformsupporting

confidence: 66%

“…This method enables complex tasks to be solved by combining different types of control synthesis techniques. We tested this approach on an intruder detection task with realistic constraints [14]. The robots had to monitor an area, detect, and follow any intruder that attempted to cross it and periodically recharge their batteries at a base station.…”

Section: Studies Conducted With the Platformmentioning

confidence: 99%

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Design and development of an inexpensive aquatic swarm robotics system

Costa

Duarte

Rodrigues

et al. 2016

OCEANS 2016 - Shanghai

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Swarm robotics is a promising approach characterized by large numbers of relatively small and inexpensive robots. Since such systems typically rely on decentralized control and local communication, they exhibit a number of interesting and useful properties, namely scalability, robustness to individual faults, and flexibility. In this paper, we detail the design and development process of a swarm robotics platform composed of autonomous surface robots, which was designed in order to study the use of robotic swarms in real-world environments. Our aquatic surface robots where manufactured using digital fabrication techniques, such as 3D printing and CNC milling, and all hardware and software has been made available as open-source, thus allowing third-parties to customize and further improve our platform.

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Section: Studies Conducted With the Platformsupporting

confidence: 66%

Section: Studies Conducted With the Platformmentioning

confidence: 99%

Design and development of an inexpensive aquatic swarm robotics system

Costa

Duarte

Rodrigues

et al. 2016

OCEANS 2016 - Shanghai

Self Cite

View full text Add to dashboard Cite

show abstract

“…behaviors [32,51,77]. In recent work [78], we have taken the first steps towards the demonstration of hierarchical control in a real robotic swarm, and demonstrate how this control approach can produce modular and flexible behaviors.…”

Section: Evolutionary Processmentioning

confidence: 99%

“…In this study, we showed how multiple evolved behaviors could be sequentially arranged in order to perform an environmental monitoring task. Future work should explore the usage of more capable techniques for combining controllers, such as hierarchical composition [51,78].…”

Section: Safetymentioning

confidence: 99%

Evolution of Collective Behaviors for a Real Swarm of Aquatic Surface Robots

et al. 2016

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Swarm robotics is a promising approach for the coordination of large numbers of robots. While previous studies have shown that evolutionary robotics techniques can be applied to obtain robust and efficient self-organized behaviors for robot swarms, most studies have been conducted in simulation, and the few that have been conducted on real robots have been confined to laboratory environments. In this paper, we demonstrate for the first time a swarm robotics system with evolved control successfully operating in a real and uncontrolled environment. We evolve neural network-based controllers in simulation for canonical swarm robotics tasks, namely homing, dispersion, clustering, and monitoring. We then assess the performance of the controllers on a real swarm of up to ten aquatic surface robots. Our results show that the evolved controllers transfer successfully to real robots and achieve a performance similar to the performance obtained in simulation. We validate that the evolved controllers display key properties of swarm intelligence-based control, namely scalability, flexibility, and robustness on the real swarm. We conclude with a proof-of-concept experiment in which the swarm performs a complete environmental monitoring task by combining multiple evolved controllers.

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“…In swarm robotics research field, several works for the covering and track-ing tasks can be found, such as those presented in [6,1,10,21,8,34,35]. However, we have found that many of these works do not take into account the special characteristics of the UAVs and therefore are not energetically applicable [6,10,21,8]. Others works, although were designed for this type of vehicle, are not applicable to the required localization and tracking tasks and are not adapted to the specific needs of non-structured environments, required in marine exploration and jellyfish blooms detection [34,35].…”

Section: Introductionmentioning

confidence: 99%

A swarm behaviour for jellyfish bloom detection

2017

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In this paper we will deal with the issue of swarm behaviour for jellyfish detection using UAVs (Unmanned Aerial Vehicles). Swarm behaviour is inspired by the functioning of biological swarms. They are characterized by being fully distributed, scalable and fault-tolerant. Initially, we will study the behaviour of jellyfish and their impact and interaction with industry. Motivated by the need to improve current detection systems, we will propose a swarm behaviour, that will be formalized with a microscopic model. We will discuss both the convergence and the scalability of the model. Finally, a macroscopic model will be provided to predict the probability that an individual is placed in a position at a given moment.

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Hybrid Control for a Real Swarm Robotics System in an Intruder Detection Task

Cited by 15 publications

References 27 publications

Design and development of an inexpensive aquatic swarm robotics system

Design and development of an inexpensive aquatic swarm robotics system

Evolution of Collective Behaviors for a Real Swarm of Aquatic Surface Robots

A swarm behaviour for jellyfish bloom detection

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