Litarature study: Difference between revisions

From Control Systems Technology Group
Jump to navigation Jump to search
Line 47: Line 47:


has a lot of interesting references and also gives some nice details about path-finding using the pheromone approach.
has a lot of interesting references and also gives some nice details about path-finding using the pheromone approach.
|3
|4
|[[Media:Qi,_Song,_Li_-_2008_-_Blackboard_Mechanism_Based_Ant_Colony_Theory_for_Dynamic_Deployment_of_Mobile_Sensor_Networks.pdf]]
|[[Media:Qi,_Song,_Li_-_2008_-_Blackboard_Mechanism_Based_Ant_Colony_Theory_for_Dynamic_Deployment_of_Mobile_Sensor_Networks.pdf]]
|-
|-
Line 53: Line 53:
|Nicolis S, Detrain C, Demolin D, et. al.
|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.  
|(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.  
|4
|[[Media:Nicolis_et_al._-_2003_-_Optimality_of_collective_choices_a_stochastic_approach.pdf]]
|-
|A hierarchical approach for primitive-based motion planning and control of autonomous vehicles
|Grymin D, Neas C, Farhood M, et. al.
|This is about finding a path to a goal. Useful since whenever a goal is first established by our swarm, we will need to find a good path (once)
|3
|3
|[[Media:Nicolis_et_al._-_2003_-_Optimality_of_collective_choices_a_stochastic_approach.pdf]]
|[[Media:Grymin,_Neas,_Farhood_-_2014_-_A_hierarchical_approach_for_primitive-based_motion_planning_and_control_of_autonomous_vehicles.pdf]]
|-
|Social Cognitive Maps, Swarm Collective Perception and Distributed Search on Dynamic Landscapes
|Ramos V, Fernandes C, Rosa A, et. al.
|Lengthy introduction which gives a more philosophical view of the connection between swarm intelligence and intelligence in general.<br>
 
Paper itself seems to give more details about how the pheromone concept can be used.<br>
 
Also mentions an other algorithm (Bacterial Foraging Optimization Algorithm) which we might want to check out, and has references to possibly useful Matlab code.
|4
|[[Media:Ramos,_Fernandes,_Rosa_-_2005_-_Social_Cognitive_Maps,_Swarm_Perception_and_Distributed_Search_on_Dynamic_Landscapes.pdf]]
|-
|Guest editorial advances in multirobot systems
|Arai T, Pagello E, Parker L, et. al.
|An overview
|2
|[[Media:Arai,_Pagello,_Parker_-_2002_-_Guest_editorial_advances_in_multirobot_systems.pdf]]
|-
|-
|}
|}


Back to: [[PRE2015_2_Groep1]]
Back to: [[PRE2015_2_Groep1]]

Revision as of 18:08, 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.

4 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. 4 Media:Nicolis_et_al._-_2003_-_Optimality_of_collective_choices_a_stochastic_approach.pdf
A hierarchical approach for primitive-based motion planning and control of autonomous vehicles Grymin D, Neas C, Farhood M, et. al. This is about finding a path to a goal. Useful since whenever a goal is first established by our swarm, we will need to find a good path (once) 3 Media:Grymin,_Neas,_Farhood_-_2014_-_A_hierarchical_approach_for_primitive-based_motion_planning_and_control_of_autonomous_vehicles.pdf
Social Cognitive Maps, Swarm Collective Perception and Distributed Search on Dynamic Landscapes Ramos V, Fernandes C, Rosa A, et. al. Lengthy introduction which gives a more philosophical view of the connection between swarm intelligence and intelligence in general.

Paper itself seems to give more details about how the pheromone concept can be used.

Also mentions an other algorithm (Bacterial Foraging Optimization Algorithm) which we might want to check out, and has references to possibly useful Matlab code.

4 Media:Ramos,_Fernandes,_Rosa_-_2005_-_Social_Cognitive_Maps,_Swarm_Perception_and_Distributed_Search_on_Dynamic_Landscapes.pdf
Guest editorial advances in multirobot systems Arai T, Pagello E, Parker L, et. al. An overview 2 Media:Arai,_Pagello,_Parker_-_2002_-_Guest_editorial_advances_in_multirobot_systems.pdf

Back to: PRE2015_2_Groep1

Retrieved from "https://dsdwiki.wtb.tue.nl/index.php?title=Litarature_study&oldid=23032"