Most valuable player: a robot device server for distributed control

Gerkey, Brian; Vaughan, Richard; Støy, Kasper; Howard, Andrew; Sukhatme, Gaurav S.; Matarić, Maja J.

doi:10.1109/iros.2001.977150

Cited by 297 publications

(204 citation statements)

References 6 publications

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“…Two metrics are of particular interest: coverage (i.e., what is the area covered by the network) and time (i.e., how long does the network take to deploy). Our experiments were conducted using the Player robot server [7] in combination with the Stage [17,6] multi-agent simulator. Stage simulates the behavior of real sensors and actuators with a high degree of fidelity, and algorithms developed using Stage can usually be transferred to real hardware with little or no modification.…”

Section: Methodsmentioning

confidence: 99%

Mobile Sensor Network Deployment using Potential Fields: A Distributed, Scalable Solution to the Area Coverage Problem

Howard

Matarić

Sukhatme

2002

Distributed Autonomous Robotic Systems 5

1,110

716

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Abstract. This paper considers the problem of deploying a mobile sensor network in an unknown environment. A mobile sensor network is composed of a distributed collection of nodes, each of which has sensing, computation, communication and locomotion capabilities. Such networks are capable of self-deployment; i.e., starting from some compact initial configuration, the nodes in the network can spread out such that the area 'covered' by the network is maximized. In this paper, we present a potential-field-based approach to deployment. The fields are constructed such that each node is repelled by both obstacles and by other nodes, thereby forcing the network to spread itself throughout the environment. The approach is both distributed and scalable.

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Section: Methodsmentioning

confidence: 99%

Mobile Sensor Network Deployment using Potential Fields: A Distributed, Scalable Solution to the Area Coverage Problem

Howard

Matarić

Sukhatme

2002

Distributed Autonomous Robotic Systems 5

1,110

716

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“…Player [10] is a server that connects robots, sensors, and control programs over the network. Gazebo [13] simulates a set of Player devices in a 3-D physically-realistic world with full dynamics.…”

Section: Validation: Coordination In Multi-robot Constructionmentioning

confidence: 99%

“…else if obstacle nearby then (8) execute obstacle avoidance (9) else if ∃a(A(x, m, a) > 0) then (10) execute action a with prob. A(x, m, a) (11) else (12) execute a random walk (13) endif (14) endrepeat (15) …”

Section: Synthesized Controllermentioning

confidence: 99%

Toward a Multi-Robot Coordination Formalism

Jones

Matarić²

2004

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Coordination is an essential characteristic of any system, either natural or artificial, that is composed of multiple interacting agents. The mechanism by which the coordination is achieved determines such properties as how robust the system is to environmental perturbations, how efficient it is in performing a given task, and, more generally, what types of coordinated tasks can be achieved. A formal understanding of these issues will permit more focused analysis of coordinated natural systems and more effective approaches to the design of coordinated artificial systems. Toward this end, we are systematically investigating coordination in the context of multi-robot systems. We present a formal framework for multi-robot system (MRS) coordination and use it to discuss and reason about coordination. Using this principled foundation, we are developing a suite of general methods by which to automatically synthesize controllers for robots constituting a MRS such that a given task is performed in a coordinated fashion. This paper presents a method for the automatic synthesis of a specific type of controller, one that retains some internal state (e.g., memory of past occurrences) but is not capable of communication. Understanding the capabilities and limitations of a coordinated system composed of individual agents with such properties contributes to the understanding of when memory alone is sufficient to achieve the desired coordination and when other capabilities, such as communication, may be necessary. We validate our formal approach to the study of coordination in a multi-robot construction task domain through the use of both physically-realistic simulations and real-robot demonstrations.

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“…Their simulation experiment was ran in a discrete grid world and assumes "local sensors." It would be interesting to see if this algorithm could operate well in a more realistic simulation environment, such as provided by Player/Stage [5], while using only small proximity sensors (ex infrared) for following robots.…”

Section: Related Workmentioning

confidence: 99%

“…Simulations were ran using the Player/Stage robot server and two-dimensional simulation environment [5]. Player/Stage is probably the highest fidelity, most realistic, robot simulation software in the world.…”

Section: Simulation Experimentsmentioning

confidence: 99%

Robotic Swarm Dispersion Using Wireless Intensity Signals

Ludwig

Gini

Distributed Autonomous Robotic Systems 7

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Summary. Dispersing swarms of robots to cover an unknown, potentially hostile area is useful to setup a sensor network for surveillance. Previous research assumes relative locations (distance and bearing) of neighboring robots are available to each robot through sensors. Many robots are too small to carry sensors capable of providing this information. We use wireless signal intensity as a rough approximation of distance to assist a large swarm of small robots in dispersion. Simulation experiments indicate that a swarm can effectively disperse through the use of wireless signal intensities without knowing the relative locations of neighboring robots.

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Most valuable player: a robot device server for distributed control

Cited by 297 publications

References 6 publications

Mobile Sensor Network Deployment using Potential Fields: A Distributed, Scalable Solution to the Area Coverage Problem

Mobile Sensor Network Deployment using Potential Fields: A Distributed, Scalable Solution to the Area Coverage Problem

Toward a Multi-Robot Coordination Formalism

Robotic Swarm Dispersion Using Wireless Intensity Signals

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