Litarature study: Difference between revisions

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|[[Media:Liu,_Chen,_Wang_-_2013_-_A_Model_of_Rescue_Task_in_Swarm_Robots_System.pdf]]
|[[Media:Liu,_Chen,_Wang_-_2013_-_A_Model_of_Rescue_Task_in_Swarm_Robots_System.pdf]]
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|Blackboard Mechanism Based Ant Colony Theory for Dynamic Deployment of Mobile Sensor Networks
|Qi G, Song P, Li K, et. al.
|Uses the "blackboard" approach to pheromones which is interesting since we probably don't want to use s physical pheromone, but a pheromone approach does seem to be highly applicable to our case<br>
has a lot of interesting references and also gives some nice details about path-finding using the pheromone approach.
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|[[Media:Qi,_Song,_Li_-_2008_-_Blackboard_Mechanism_Based_Ant_Colony_Theory_for_Dynamic_Deployment_of_Mobile_Sensor_Networks.pdf]]
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|Optimality of collective choices: a stochastic approach
|Nicolis S, Detrain C, Demolin D, et. al.
|(referenced by [Liu, Chen, Wang]) It's the description of the behaviour of ants on which the model in [Liu, Cheng, Wang] is based. It also gives optimal choices for pheromones.
|3
|[[Media:Nicolis_et_al._-_2003_-_Optimality_of_collective_choices_a_stochastic_approach.pdf]]
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Revision as of 17:56, 29 November 2015

Literature Study

Each peace of literature found will be graded from 1 to 5 regarding relevance. 1 being considerd irrelevant and 5 being considered extremely relevant.

Title: Authors: Short Explenation: Relevance Grade: PDF File
The TAM: abstracting complex tasks in swarm robotics research Arne Brutschy, Lorenzo Garattoni,Manuele Brambilla,Gianpiero Francesca,Giovanni Pini,Marco Dorigo and Mauro Birattari Proposes an approach to abstract complex tasks in swarm robotics research, using TAM. 2 Media:The_TAM.pdf
Ad Hoc Communication in Teams of Mobile Robots Using ZigBee Technology AMADEU FERNANDES, MICAEL S. COUCEIRO, DAVID PORTUGAL, JOAO MACHADO SANTOS, RUI P. ROCHA The main aim of this paper is to implement and validate ad hoc wireless

communication functions between robotic teammates using the ZigBee technology.

4 Media:Zigbee.pdf
The task allocation model based on repuattion for the heterogeneous multi-robot collaboration system Zhiguo Shi, Jumming Wei, Xujian Wei, et. al. Article about assigning reputation to members on the swarm. Not useful to us, but has some nice references I want to check out. 1 Media:Zhiguo_Shi_et_al._-_2010_-_The_task_allocation_model_based_on_reputation_for_the_heterogeneous_multi-robot_collaboration_system.pdf
A Model of Rescue Task in Swarm Robots System Liu B, Chen P, Wang G, et. al. Heavily inspired by the behaviour of ants:

It describes a system in which a large swarm of robots moves pieces of "ruin piles" to "free space" communicating - inspired by the workings of an ant colony - by "feromones" which guide the robots to the piles and which decide the probability of a certain robot being assigned to a specific pile.

Strongly related
Doesn't seem to consider more than one robot moving the same object so still have to do that ourselves
works much better for very large swarms

5 Media:Liu,_Chen,_Wang_-_2013_-_A_Model_of_Rescue_Task_in_Swarm_Robots_System.pdf
Blackboard Mechanism Based Ant Colony Theory for Dynamic Deployment of Mobile Sensor Networks Qi G, Song P, Li K, et. al. Uses the "blackboard" approach to pheromones which is interesting since we probably don't want to use s physical pheromone, but a pheromone approach does seem to be highly applicable to our case

has a lot of interesting references and also gives some nice details about path-finding using the pheromone approach.

3 Media:Qi,_Song,_Li_-_2008_-_Blackboard_Mechanism_Based_Ant_Colony_Theory_for_Dynamic_Deployment_of_Mobile_Sensor_Networks.pdf
Optimality of collective choices: a stochastic approach Nicolis S, Detrain C, Demolin D, et. al. (referenced by [Liu, Chen, Wang]) It's the description of the behaviour of ants on which the model in [Liu, Cheng, Wang] is based. It also gives optimal choices for pheromones. 3 Media:Nicolis_et_al._-_2003_-_Optimality_of_collective_choices_a_stochastic_approach.pdf

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