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Article Usefulness
Each peace of literature found with an interesting abstract will be graded from 1 to 5 regarding relevance. 1 being considerd irrelevant and 5 being considered extremely relevant.
Adaptive collective decision-making in
 
limited robot swarms without
{| border="1" cellpadding="5" cellspacing="0" align="center" style="margin-left: 3em;"
communication Not useful
|-
Encoder-free odometric system for autonomous microrobots Not useful, to complicated
| width="325" | '''Title:'''
Collective energy homeostasis in a large-scale micro robotic swarm Not applicable
| width="325" | '''Authors:'''
Specialization and generalization of robot behaviour in swarm
| width="325" | '''Short Explenation:'''
energy foraging
| width="100" | '''Relevance Grade:'''
Not applicable
| width="100" | '''PDF File'''
Re-embodiment of Honeybee Aggregation Behavior
|-
in an Artificial Micro-Robotic System
| The TAM: abstracting complex tasks in swarm robotics research
Not useful
| Arne Brutschy, Lorenzo Garattoni,Manuele Brambilla,Gianpiero Francesca,Giovanni Pini,Marco Dorigo and Mauro Birattari
Auton Agent Multi-Agent Syst (2009) 18:133–155
| Proposes an approach to abstract complex tasks in swarm robotics research, using TAM.
DOI 10.1007/s10458-008-9058-5
|2
Get in touch: cooperative decision making based
|[[Media:The_TAM.pdf]]
on robot-to-robot collisions
|-
Not useful
|Ad Hoc Communication in Teams of Mobile Robots Using ZigBee Technology
An Analytical and Spatial Model of Foraging
|AMADEU FERNANDES, MICAEL S. COUCEIRO, DAVID PORTUGAL, JOAO MACHADO SANTOS, RUI P. ROCHA
in a Swarm of Robots
|The main aim of this paper is to implement and validate ad hoc wireless
Not useful, too complicated
communication functions between robotic teammates using the ZigBee technology.
Trophallaxis among swarm-robots:
|4
A biologically inspired strategy for swarm robotics
|[[Media:Zigbee.pdf]]
Useful, main topic: communication
|-
New Principles of Coordination in Large-scale
|The task allocation model based on repuattion for the heterogeneous multi-robot collaboration system
Micro- and Molecular-Robotic Groups
|Zhiguo Shi, Jumming Wei, Xujian Wei, et. al.
Maybe
|Article about assigning reputation to members on the swarm. Not useful to us, but has some nice references I want to check out.
Evolving communicating agents that integrate information over time: a real robot experiment Not useful
|1
Self-Organisation and Communication in Groups of Simulated and Physical Robots Useful
|[[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:<br>
 
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.<br>
 
Strongly related<br>
Doesn't seem to consider more than one robot moving the same object so still have to do that ourselves <br>
works much better for very large swarms<br>
|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<br>
 
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.<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]]
|-
|Swarm intelligence and stigmergy: robotic implementation of foraging behavior
|Edelen M
|Thesis referenced by [Liu, Chen, Wang] http://drum.lib.umd.edu/handle/1903/107 <br>
Quite a lot of info (a whole book), might be useful for details if we get stuck but don't want to read it in its entirety
|3
|
|-
|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]]
|-
|Research Advance in Swarm Robotics
|Tan Y, Zheng Z
|An overview
|2
|[[Media:Tan,_Zheng_-_2013_-_Research_Advance_in_Swarm_Robotics.pdf]]
|-
|Advanced swarm robots addressing innovative tasks such as assembly, search, rescue, mapping, communication, aerial and other original applications
|Richard Bloss
|A really short overview
|1
|[[Media:Advanced_swarm_robots_addressing_innovative_tasks_such_as_assembly,_search,_rescue,_mapping,_communication,_aerial_a.pdf]]
|-
|Integrated multi-agent system framework: decentralised search, tasking and tracking
|He Z, Su R, Meng W, et. al.
|Mostly for finding and tracking moving targets
|1
|[[Media:He_et_al._-_2015_-_Integrated_multi-agent_system_framework_decentralised_search,_tasking_and_tracking.pdf]]
|-
|Multiple targets enclosure by robotic swarm
|Kubo M, Sato H, Yoshimura T, et. al.
|Paper claims it is useful for disaster sites, but I'm not sure why.
|2
|[[Media:Kubo_et_al._-_2014_-_Multiple_targets_enclosure_by_robotic_swarm.pdf]]
|-
|Benchmark of swarm robotics distributed techniques in a search task
|Couceiro M, Vargas P, Rocha R, et. al.
|Compairs different search algorithms for swarms
|3 or 4
|[[Media:Couceiro_et_al._-_2014_-_Benchmark_of_swarm_robotics_distributed_techniques_in_a_search_task.pdf]]
|-
|}
 
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Latest revision as of 10:05, 30 November 2015

Each peace of literature found with an interesting abstract 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
Swarm intelligence and stigmergy: robotic implementation of foraging behavior Edelen M Thesis referenced by [Liu, Chen, Wang] http://drum.lib.umd.edu/handle/1903/107

Quite a lot of info (a whole book), might be useful for details if we get stuck but don't want to read it in its entirety

3
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
Research Advance in Swarm Robotics Tan Y, Zheng Z An overview 2 Media:Tan,_Zheng_-_2013_-_Research_Advance_in_Swarm_Robotics.pdf
Advanced swarm robots addressing innovative tasks such as assembly, search, rescue, mapping, communication, aerial and other original applications Richard Bloss A really short overview 1 Media:Advanced_swarm_robots_addressing_innovative_tasks_such_as_assembly,_search,_rescue,_mapping,_communication,_aerial_a.pdf
Integrated multi-agent system framework: decentralised search, tasking and tracking He Z, Su R, Meng W, et. al. Mostly for finding and tracking moving targets 1 Media:He_et_al._-_2015_-_Integrated_multi-agent_system_framework_decentralised_search,_tasking_and_tracking.pdf
Multiple targets enclosure by robotic swarm Kubo M, Sato H, Yoshimura T, et. al. Paper claims it is useful for disaster sites, but I'm not sure why. 2 Media:Kubo_et_al._-_2014_-_Multiple_targets_enclosure_by_robotic_swarm.pdf
Benchmark of swarm robotics distributed techniques in a search task Couceiro M, Vargas P, Rocha R, et. al. Compairs different search algorithms for swarms 3 or 4 Media:Couceiro_et_al._-_2014_-_Benchmark_of_swarm_robotics_distributed_techniques_in_a_search_task.pdf

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