Acoustic Localization Robot Team Members: Dave Shelley Phil Poletti Joe Massey.
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Transcript of Acoustic Localization Robot Team Members: Dave Shelley Phil Poletti Joe Massey.
Acoustic Localization Robot
Team Members:Dave Shelley
Phil PolettiJoe Massey
Agenda
[Desired Results] [Achieved Results] [Lessons Learned] [Possible Improvements] [Recorded Demonstration] [Live Demonstration]
Desired Results
Key Desired Metrics to Achieve: Utilize quasi- three dimensional
microphone array to capture audio in real-time.
Calculate location of source utilizing beamforming algorithm
Laser points to location in space through use of Lego Mindstorm NXT through pitch and yaw movement.
Achieved Results
Key Metrics Achieved Utilizes quasi- three dimensional microphone
array to capture audio in real-time. Calculates location of source utilizing
beamforming algorithm• Instead of using a beamforming algorithm, an
amplitude vectoring algorithm was utilized • Beamforming algorithm placed overwhelmingly large
processing constraints on processor.• Did not provide far superior results as expected• Amplitude vectoring algorithm only provides a maximum
pitch and yaw resolution of 90 degrees Laser points to location in space through
use of Lego Mindstorm NXT
Lessons Learned[Issue] [Specific problems]
[Poor Quality of Purchased
Components]
USB Microphone Decided to use USB Sound Card in conjunction with 3.5mm analog
microphone•Poor Frequency Response
•Inconsistent gain across different mics
[Undesired Environment
Noise]
Acoustical Inconsistencies Shape of room causes undesired acoustic reflections Electronics utilized for project implementation cause undesired interference
[Beamforming Algorithm]
Algorithm causes large system latencies Complexity of algorithm makes implementation difficult Originally intended for use with 100+ microphones over a large spatial
region
[USB Interfacing Problems]
Operating System Permissions USB Hub issues
Possible Improvement
[Improvement] [Best method for implementation]
[TDOA (Time Delay of Arrival)]
GCC –PHAT (Cross Correlation with Phase Transform) would provide much higher resolution, detecting phase differences, rather than amplitude differences between microphones.
Additional Microphones]
Currently, the amplitude vectoring algorithm only allows for 90 degrees maximum of resolution.
More microphones in the X and Y planes would allow for much higher resolution.
[Threading] Utilize threading of all processes to streamline
[Error Checking] Compare five or more concurrent runs and determine location based on histogram of five runs
[Laser Driver] Implement a voltage regular to more easily pulse the laser without using Lego NXT Motor Drivers.
For Further Information:
For a complete explanation of our project as
well as compilations of all our code,
proceed to:
http://code.google.com/p/acoustic-localization-robot/
Hardware Components Utilized
Dell Inspiron
2.0 GHz Core2Duo
800MHz Front Side Bus
2 GB DDR2 RAM
Linux Ubuntu v9.10
6x USB Microphone Array Lego NXT
Microcontroller with Laser Turret
Breakdown of Debug Screen
Band Pass Filter Coefficients
Amplitude in dB of highest frequency
on each mic
Location of Max Amplitude
Correct USB Handshake to Lego
NXT
Recorded Demonstration
Shortcut to Recorded Demonstration
Live Demonstration