Pattern Formation by Oblivious Asynchronous Mobile Robots

Fujinaga, Nao; Yamauchi, Yukiko; Ono, Hiroyuki; Kijima, Shuji; Yamashita, Masafumi

doi:10.1137/140958682

Cited by 86 publications

(92 citation statements)

References 17 publications

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“…They never cross, if the sum of their distances is smaller than the other way. The proof is given in [19]. As shown in fig.…”

Section: Collision Avoidance Algorithmmentioning

confidence: 99%

“…Assume each robot has one neighbor at least. According to Lemma 1, we propose a collision avoidance algorithm based on [10], [11], [14]- [16], [19], which consists of 6 steps: (1) Positions P ci (x ci , y ci ) in initial group are separated into .. = y f i+j , all of these positions P f i , P f i+1 , ...P f i+j in each set of final group are reordered according to x f i , and at the same time the positions with the same subscripts P ci , P ci+1 , ...P ci+j in the associated set of initial group also are reordered according to x ci . (4) Similar to (3), if y ci − y ci+k < ε, (k = 1, ..., j), P ci , P ci+1 , ...P ci+j of each set are reordered again according to x ci , and P f i , P f i+1 , ...P f i+j coordinated positions in final group are also reordered according to fig.…”

Section: Collision Avoidance Algorithmmentioning

confidence: 99%

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Pattern formation for a fleet of AUVs based on optical sensor

Wang¹,

Zerr

Thomas

et al. 2017

OCEANS 2017 - Aberdeen

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Abstract-During the past decades, multi-robot systems have been studied deeply and have demonstrated their advantages in conducting autonomous missions, particularly in underwater environment. When using multiple robots, high cost single sensor can be replaced by many coordinated low cost sensors, such as optical sensors used in our work for acquiring relevant data and coordinating the fleet of robots. In this paper, we propose a coordination algorithm for pattern formation (the shape of the fleet), which includes a new predefined pyramid pattern independent on the number of robots and an associated formation control strategy for building and maintaining this pyramid without collision among robots and without external assistant in non-obstacle situation. The formation control strategy consists of three steps: (1) a common frame is built after the exchange of local information extracted from visual servoing (VS) and compass of each robot; (2) a pyramid frame is established from the distribution of robots, and whose orientation is defined by one of the two following methods: one based on principal component analysis (PCA) and the other one based on an intermediate circle pattern (CP); (3) the kernel part is the collision avoidance strategy (CA) which is realized by optimally matching up positions in the distribution and the pyramid, and planning the straight nonintercrossed trajectories. At last, robots build the pyramid along the straight trajectory. During the whole process, except the information exchange for establishing the common frame, robots do not need communication as they have the same algorithms. Until now the performance of the formation control strategy is demonstrated with 4 to 6 robots in Blender based on dynamic equations of real underwater robots.

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“…They never cross, if the sum of their distances is smaller than the other way. The proof is given in [19]. As shown in fig.…”

Section: Collision Avoidance Algorithmmentioning

confidence: 99%

Section: Collision Avoidance Algorithmmentioning

confidence: 99%

Pattern formation for a fleet of AUVs based on optical sensor

Wang¹,

Zerr

Thomas

et al. 2017

OCEANS 2017 - Aberdeen

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“…In literature, the researchers have established various theoretical models for MRS. Based on those models, the fundamental coordination problems are studied. Specifically, the theoretical models are divided into fully-synchronous, semi-synchronous, and asynchronous [38] and fundamental coordination problems include gathering [39], pattern formation [35,40], flocking [41], and so on. We categorize the local coordination in MRS according to three criteria, namely, system model, and robot ability, the problem as shown in Figure 3.…”

Section: Local Coordination In Multi-robot Systemsmentioning

confidence: 99%

CPS-Based Smart Warehouse for Industry 4.0: A Survey of the Underlying Technologies

et al. 2018

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This paper discusses how the state-of-the-art techniques in cyber-physical systems facilitate building smart warehouses to achieve the promising vision of industry 4.0. We focus on four significant issues when applying CPS techniques in smart warehouses. First, efficient CPS data collection: when limited communication bandwidth meets numerous CPS devices, we need to make more effort to study efficient wireless communication scheduling strategies. Second, accurate and robust localization: localization is the basis for many fundamental operations in smart warehouses, but still needs to be improved from various aspects like accuracy and robustness. Third, human activity recognition: human activity recognition can be applied in human-computer interaction for remote machine operations. Fourth, multi-robot collaboration: smart robots will take the place of humans to accomplish most tasks particularly in a harsh environment, and smart and fully-distributed robot collaborating algorithms should be investigated. Finally, we point out some challenging issues in the future CPS-based smart warehouse, which could open some new research directions.

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“…In [5], Das et al investigated the problem of forming a sequence of patterns in a given order. In [3,9], the problem was studied allowing the pattern to have multiplicities. In [4,9] the so-called EMBEDDED PATTERN FORMATION problem was studied where the pattern to be formed is provided as a set of visible points in the plane.…”

Section: Earlier Workmentioning

confidence: 99%

“…In [3,9], the problem was studied allowing the pattern to have multiplicities. In [4,9] the so-called EMBEDDED PATTERN FORMATION problem was studied where the pattern to be formed is provided as a set of visible points in the plane. Recently in [10], the pattern formation problem was studied on an infinite grid for robots with limited visibility.…”

Section: Earlier Workmentioning

confidence: 99%

Arbitrary Pattern Formation on Infinite Grid by Asynchronous Oblivious Robots

Bose

Adhikary

Kundu

et al. 2018

WALCOM: Algorithms and Computation

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The ARBITRARY PATTERN FORMATION problem asks to design a distributed algorithm that allows a set of autonomous mobile robots to form any specific but arbitrary geometric pattern given as input. The problem has been extensively studied in literature in continuous domains. This paper investigates a discrete version of the problem where the robots are operating on a two dimensional infinite grid. The robots are assumed to be autonomous, identical, anonymous and oblivious. They operate in Look-Compute-Move cycles under a fully asynchronous scheduler. The robots do not agree on any common global coordinate system or chirality. We have shown that a set of robots can form any arbitrary pattern, if their starting configuration is asymmetric.

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Pattern Formation by Oblivious Asynchronous Mobile Robots

Cited by 86 publications

References 17 publications

Pattern formation for a fleet of AUVs based on optical sensor

Pattern formation for a fleet of AUVs based on optical sensor

CPS-Based Smart Warehouse for Industry 4.0: A Survey of the Underlying Technologies

Arbitrary Pattern Formation on Infinite Grid by Asynchronous Oblivious Robots

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