Difference between revisions of "2D Robotic Movement"

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The freedom which 2D movement provides makes the problem of deciding upon physical limitations for movement important in creating an algorithm to optimize microphone placement. If for example the sound source is within the 2D surface in which the robots are allowed to travel, we saw that the highest resolution results from moving the microphones very close to the source and surrounding it, as can be seen from the configuration of the web of points********, with the highest density in the center. The challenges change though when the system is limited to say a rectangular area and the source is located outside of this region. The optimal configuration might then be to rotate the robots to collectively face the source, approach the physical boundary, and the source itself, as closely as possible, and then converge/diverge to until an optimal position is found. For this reason we found it important to keep the specific physical constraints in mind when designing an algorithm for adaptive movement in 2D.
 
The freedom which 2D movement provides makes the problem of deciding upon physical limitations for movement important in creating an algorithm to optimize microphone placement. If for example the sound source is within the 2D surface in which the robots are allowed to travel, we saw that the highest resolution results from moving the microphones very close to the source and surrounding it, as can be seen from the configuration of the web of points********, with the highest density in the center. The challenges change though when the system is limited to say a rectangular area and the source is located outside of this region. The optimal configuration might then be to rotate the robots to collectively face the source, approach the physical boundary, and the source itself, as closely as possible, and then converge/diverge to until an optimal position is found. For this reason we found it important to keep the specific physical constraints in mind when designing an algorithm for adaptive movement in 2D.
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[[File:robotmovement.jpg|center]]

Revision as of 07:37, 30 April 2010

<sidebar>Robotic Sensing: Adaptive Robotic Control for Improved Acoustic Source Localization in 2D Nav</sidebar>

2D Overview

The goal of this semester’s progress was to extend the robotic system from 1D adaptive movement to allow it to move freely on a 2D surface. Doing this provides the system with a number of different types of movement it can use in order to optimize microphone placement. Working with 1 dimensional movement, the robots could only shift sideways and converge/diverge. With 2D movement the robots can physically approach the source, point each of their microphone pairs to best face the source individually, and rotate around themselves to collectively face the source, in addition to sideways movement and converging/diverging. This provides a much more robust system for resolution improvement compared to using only 1D movement.

The freedom which 2D movement provides makes the problem of deciding upon physical limitations for movement important in creating an algorithm to optimize microphone placement. If for example the sound source is within the 2D surface in which the robots are allowed to travel, we saw that the highest resolution results from moving the microphones very close to the source and surrounding it, as can be seen from the configuration of the web of points********, with the highest density in the center. The challenges change though when the system is limited to say a rectangular area and the source is located outside of this region. The optimal configuration might then be to rotate the robots to collectively face the source, approach the physical boundary, and the source itself, as closely as possible, and then converge/diverge to until an optimal position is found. For this reason we found it important to keep the specific physical constraints in mind when designing an algorithm for adaptive movement in 2D.

Robotmovement.jpg