2004
DOI: 10.1007/978-3-540-28646-2_10
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Cooperative Transport of Objects of Different Shapes and Sizes

Abstract: Abstract. This paper addresses the design of control policies for groups of up to 16 simple autonomous mobile robots (called s-bots) for the cooperative transport of heavy objects of different shapes and sizes. The s-bots are capable of establishing physical connections with each other and with the object (called prey). We want the s-bots to self-assemble into structures which pull or push the prey towards a target location. The s-bots are controlled by neural networks that are shaped by artificial evolution. … Show more

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Cited by 33 publications
(20 citation statements)
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“…For example, in this paper, we reported on a trial where a group of 16 robots self-organised into a cyclic structure, which entirely surrounded the object (without being physically connected to it). This structure was functional -it pulled the object like an artificial rope [for a collection of video recordings, see Groß and Dorigo (2008b)]. The drawback of this strategy is that the solution search space is relatively complex and large.…”
Section: Discussionmentioning
confidence: 99%
“…For example, in this paper, we reported on a trial where a group of 16 robots self-organised into a cyclic structure, which entirely surrounded the object (without being physically connected to it). This structure was functional -it pulled the object like an artificial rope [for a collection of video recordings, see Groß and Dorigo (2008b)]. The drawback of this strategy is that the solution search space is relatively complex and large.…”
Section: Discussionmentioning
confidence: 99%
“…Although robot teams working toward a common goal has been studied intensively, focus has been on enabling the robots to collect global information by exploring their environment [13,26] or collectively manipulating an object that could not be manipulated by a single robot [19,17]. This work points to a new way in which robots can help one another: they can share their experiences by sharing self-models.…”
Section: Discussionmentioning
confidence: 99%
“…The best of the evolved controllers efficiently transported the object as required. Furthermore, these controllers proved robust with respect to variations in the size and shape of the object they had to transport [8].…”
Section: Cooperative Transportmentioning
confidence: 99%