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OBS

by Sifat Momen (Submitted: 07/28/2009)

[screen shot]

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WHAT IS IT?

This is a simple model that demonstrates how agents can avoid obstacles and find targets autonomously using the potential field approach.

HOW IT WORKS

The model uses the potential field approach to avoid obstacles and find targets. Such mechanisms could be well used in exploring the behaviour of ants trying to find a food source or the nest on their way back home.

Imagine each ant/agent/robot to be positively charged, obstacle(s) to be positively charged and the target to be negatively charged, the agents would then avoid the obstacle and reach the target.

The model embraces the concept of potential field from electrostatics and also a very popular mechanism in path planning of agents. The Potential field due to the target is modelled using the following equation:

    V = Vg * exp (-lambda * Xg)

& that due to the obstacle by

    V = -Vo * exp (-lambda * Xo)

where

    Vg is the potential field at the location of the goal/target
V0 is the potential field at the location of the obstacle
Xg is the distance from the goal, and
Xo is the distance from the obstacle

HOW TO USE IT

Press the Setup button to setup the environment and the Go button to start and stop the simulation

THINGS TO NOTICE

Check how the convergence time varies with different values of Vg and Vo

EXTENDING THE MODEL

Maybe including more objects of different shapes would be an interesting thing to look at.

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