Monthly Archives: April 2012

There She Goes

This entry is part 4 of 10 in the series Android Robot
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Connecting DC motors to the IOIO through the TB6612FNG, a motor driver break out board

This entry is part 3 of 10 in the series Android Robot

The IOIO has the capability to output Pulse Width Modulated (PWM) signals on its pins. You can vary the duty cycle of PWM signals to control the speed of DC motors. It’s recommended that you don’t connect the IOIO directly … Continue reading

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Power to the IOIO

This entry is part 2 of 10 in the series Android Robot

The IOIO board (unlike the Arduino) does not come with headers attached on it, so you’ve got to solder them on yourself. Use the Arduino headers (again available from Little Bird Electronics) and solder them on to the board. I’ve … Continue reading

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Setting Up Your First IOIO Project In Eclipse

This entry is part 1 of 10 in the series Android Robot

If you’ve already been programming Android apps with Eclipse, as I have, you would’ve thought that the downloading and running of the HelloIOIO app would’ve been a synch. As with everything software, you would’ve been wrong. It is just impossible … Continue reading

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SURF Feature Descriptors on Python OpenCV

This entry is part 1 of 1 in the series Image Feature Descriptors

This is a test of SURF features (http://en.wikipedia.org/wiki/SURF, claimed to be faster than the original SIFT feature descriptors) on Python OpenCV. Parameters used were: (0, 300, 3, 4) 0: (basic, 64-element feature descriptors) hessian threshold: 300 number of octaves: 3 … Continue reading

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Occupancy Grid

This entry is part 3 of 3 in the series Python Robotics Simulator

The easiest way for a robot to map its environment is using an occupancy grid. As the robot moves through its environment, the readings returned from its laser range finder (LRF) at different angles around it are marked off on … Continue reading

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Particle Filter Localization for a Simulated Mobile Robot

This entry is part 2 of 3 in the series Python Robotics Simulator

This simulation shows a robot (red) moving through a simulated environment and a Particle Filter (PF) trying to localize it in that environment. Initially, the particles (shown in different shades of grey indicating their probabilities) do not know the location … Continue reading

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Simulated Laser Range Finder Readings Using Python & OpenCV

This entry is part 1 of 3 in the series Python Robotics Simulator

This is my first simulation using Python + OpenCV. It rotates a robot in a SLAM Map to get 9 simulated range (laser range finder) readings that it can then use to localize itself on that map. Watch the video … Continue reading

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Setting up OpenCV 2.2 with Python on OS X

This post should be useful to Mac users who want to get OpenCV up and running with Python. I’ve recently migrated to an older (2010 refurbished) MacBook Air (from a 2011 MacBook Pro) which runs OS X 10.6.8 (The Pro … Continue reading

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