Proceedings 2005 IEEE Swarm Intelligence Symposium, 2005. SIS 2005.
DOI: 10.1109/sis.2005.1501639
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Probabilistic aggregation strategies in swarm robotic systems

Abstract: In this study, a systematic analysis of probabilistic aggregation strategies in swarm robotic systems is presented. A generic aggregation behavior is proposed as a combination of four basic behaviors: obstacle avoidance, approach, repel, and wait. The latter three basic behaviors are combined using a three-state finite state machine with two probabilistic transitions among them. Two different metrics were used to compare performance of strategies. Through systematic experiments, how the aggregation performance… Show more

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Cited by 102 publications
(78 citation statements)
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“…In robotics, aggregation is deployed to get robots in a swarm sufficiently close together and communicate to each other with limited range. The self-organized aggregation behaviors for swarm robotic systems is essential to form a robot cluster and perform needed communication tasks (Soysal and Ş ahin 2005). Additionally, aggregation is used for swarm robotic behaviors such as self-assembly and pattern formation (Erol and Ec 2007).…”
Section: Swarm Roboticsmentioning
confidence: 99%
“…In robotics, aggregation is deployed to get robots in a swarm sufficiently close together and communicate to each other with limited range. The self-organized aggregation behaviors for swarm robotic systems is essential to form a robot cluster and perform needed communication tasks (Soysal and Ş ahin 2005). Additionally, aggregation is used for swarm robotic behaviors such as self-assembly and pattern formation (Erol and Ec 2007).…”
Section: Swarm Roboticsmentioning
confidence: 99%
“…Garnier et al [13] adopted a probabilistic approach to achieve aggregation within a swarm of 20 physical Alice robots in homogeneous environments. Soysal and Sahin [14] suggested a probabilistic aggregation method in which state finite machine is used to combine a set of simple behaviors (obstacle avoidance, approach, repel, and wait). Ando et al [15] proposed a deterministic approach using graph theory to study aggregation in a group of mobile robots with a limited sensing range.…”
Section: Related Workmentioning
confidence: 99%
“…Stochastic characteristic of swarm algorithms leads to use a probabilistic modelling to depict the collective behaviour of the swarm systems [20]. To that end, various models from macroscopic behaviours of swarms have been proposed in [10,13,14].…”
Section: Introductionmentioning
confidence: 99%