Communication Strategies in Multi-robot Search and Retrieval: Experiences with MinDART

Rybski, Paul E.; Larson, A.C.; Veeraraghavan, Harini; LaPoint, M.A.; Gini, Maria

doi:10.1007/978-4-431-35873-2_31

Cited by 23 publications

(21 citation statements)

References 17 publications

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“…In that work, robots communicated explicitly with one another. Both implicit and explicit communication strategies have been studied in the context of foraging [1,2,11,10]. The robots in this work do not have explicit communication capabilities and other robots are merely perceived as obstacles.…”

Section: Related Workmentioning

confidence: 99%

On foraging strategies for large-scale multi-robot systems

Shell

Matarić

2006

2006 IEEE/RSJ International Conference on Intelligent Robots and Systems

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Abstract-Physical interference limits the utility of largescale multi-robot systems. We present an empirical study of the effects of such interference in systems with hundreds of minimalist robots. We consider the canonical multi-robot foraging task, and define a new parametrized controller. This controller allows for evaluation of spatial arbitration strategies along a continuum with the traditional homogeneous and bucket-brigading algorithms at each end. We present data from thousands of simulations which suggests that methods surprisingly close to homogeneous foraging, but augmented with limited arbitration, can improve both performance and reliability.

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Section: Related Workmentioning

confidence: 99%

On foraging strategies for large-scale multi-robot systems

Shell

Matarić

2006

2006 IEEE/RSJ International Conference on Intelligent Robots and Systems

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“…Ijspeert et al (2001) show how in a strictly collaborative task (i.e., a task where cooperation is strictly required for the goal achievement) a simple form of direct communication can enhance the performance of the system. Similarly to the already mentioned work of Balch and Arkin (1994), Rybski et al (2004) study the influence of different forms of communication on the performance of a collective robotic system in a foraging task.…”

Section: From Insects To Robotsmentioning

confidence: 94%

Self-organisation and communication in groups of simulated and physical robots

Trianni

Dorigo

2006

Biol Cybern

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In social insects, both self-organisation and communication play a crucial role for the accomplishment of many tasks at a collective level. Communication is performed with different modalities, which can be roughly classified in three classes: indirect (stigmergic) communication, direct interactions and direct communication. The use of stigmergic communication is predominant in social insects (e.g., the pheromone trails in ants), where however also direct interactions (e.g., antennation in ants) and direct communication (e.g., the waggle dance in honey bees) can be observed. Taking inspiration from insect societies, we present an experimental study of self-organising behaviours for a group of robots, which exploit communication to coordinate their activities. Artificial evolution is responsible for the synthesis in a simulated environment of the robot's neural controllers, which are subsequently tested on physical robots. We study different communication strategies among the robots: no direct communication, handcrafted signalling and a completely evolved approach. We show that the latter is the most efficient, suggesting that artificial evolution can produce behaviours that are more adaptive than those obtained with conventional design methodologies. Moreover, we show that the evolved controllers produce a self-organising systems that is robust enough to be tested on physical robots, notwithstanding the huge gap between simulation and reality.

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“…Direct communication can be used to reduce the effects of interference in potentially crowded areas such as the nest [76], to facilitate finding a place of interest such as an item source [78,79] or the nest [80], or to implement mechanisms of cooperative transport of items [81,82,83]. Communication can take place also by simply sensing the relative position of nearby robots [84], or even using contact sensing [85].…”

Section: Direct Communicationmentioning

confidence: 99%

“…Rybski et al [79] implemented two communication strategies where robots turn on a light source to which other robots are attracted; the purpose of these strategies is to attract robots toward item sources. In the first strategy, called reflexive communication, a robot in the process of picking up an item signals its status with light emission; in the second strategy, called deliberate communication, a robot which detects an item but cannot collect it because it is carrying another item stops near the detected item and signals its presence for a fixed time duration (trying to "recruit" other robots to pick up the detected item) before returning to the nest.…”

Section: Other Cooperation Mechanismsmentioning

confidence: 99%