BLOG KEYWORDS: Multi-robot system, Multi-agent architecture, Microcontroller programming, Sensor data fusion, Feedback control, mobile robotics, Centralized/Decentralized wireless communication, BDI (Belief-Desire-Intention), MA3-LM (Multi-Agent Assignment Algorithem Local Mediation), A-QoS (Application Quality-of-Service), Embedded-robot technology.

Thursday, March 29, 2007

First robot kit arrived

Happy news, the first robot kit (the BoeBot from Parallax Inc.) has arrived yesterday. Various photos has been taken just now, I did not do digital enhancement but just stack them on one page and make it published. Due to exam preparation, I will not assembly the kit until all exams are over (which is about one month later).


I think the second robot kit should be coming soon, may be in half month time, which is a bigger and more powerful one, I will reveal ‘him’ to you by the time.

Thursday, March 22, 2007

Abstract Model to deploy MA3/MA3-LM on multi-robot system using BDI concepts

After entering the station, each robot will evaluate itself for completing every task based on sensor input data (identify relative location, task parameters etc.) and its own abilities, and hence generates a set of A-QoS (Application Quality-of-service) number, such that each robot will believe[B] all tasks can be achieved to a certain degree.

Station 1 was created for some other understanding purpose; let's not consider it for now.


For Station 2:

Upon perceiving that, all robots in the group will have its own desired task which is the local maximum value (i.e. max number of the row), and they will send their set of A-QoS value to the leader robot (one having better computation power or arbitrarily selected) through a communication channel, leader will compute out a set of A-QoS number such that the maximum group gain will be achieved, each robot then will be assigned to attempt one particular task.

For Station 3 (MA3-LM) :
All robots will be initiated to an arbitrary task according to indexing or some other ways (i.e. one arbitrary no. is selected in the row), in the way that robots and tasks are all engaged and one-to-one mapped, then each robot will broadcast its unengaged A-QoS values (i.e. the other two numbers in the row), if there is a positive gain in A-QoS value the robots will have its desire(s)[D] to exchange the tasks with the other robot(s), thereafter if both robots have desire to exchange tasks then it will become both robots’ intention[I]. Subsequently, a new round of BDI reasoning will take place and will continue until no robot has desire to exchange, then exchange will take place.


A-QoS: Application Quality-of-Service
BDI: Belief-Desire-Intention
MA3: Multi-Agent Assignment Algorithm
MA3-LM: Multi-Agent Assignment Algorithm Local Mediation





REFERENCES

  • Seow T.K. AND How K.Y., 2002, Collaborative Assignment: A Multiagent Negotiation Approach Using BDI Concepts
  • Seow T.K. and Sim K.M., 2006, Decentralized Assignment Reasoning Using Collaborative Local Mediation

Saturday, March 17, 2007

Matlab and Simulink exercise

For a good control system design, the system overall performance and system stability are the key measurements, Matlab and Simulink are certainly the good tools to fit in this needs. I have watched a few webinars, which utilizing Matlab, Simulink and Stateflow in automobile, aerospace and large scale model design are really awesome.


Here let me try on a few examples to get my hands warm, I think later on there will be a deployment of these awesome tools in my project.


Blow is a picture shows a very simple close loop control system exercise I did. (REFERENCE: Leonard N.E. AND Levine W. S., 1999, Using Matlab to analyze and design control system 2nd edition)





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