Projects:2015s1-01 LaunchBox - Revision history

A1627418: /* Sun Centroid Calculation Algorithm */

2015-10-23T02:24:27Z

‎Sun Centroid Calculation Algorithm

A1627418: /* Project Outcome */

2015-10-23T02:21:20Z

‎Project Outcome

A1627418: /* Internal Communications Development */

2015-10-23T02:19:25Z

‎Internal Communications Development

A1627418: /* Internal Communications Development */

2015-10-23T02:17:07Z

‎Internal Communications Development

A1627418: /* Further Developments */

2015-10-23T02:13:04Z

‎Further Developments

A1627418: /* External Communications Development */

2015-10-23T02:05:26Z

‎External Communications Development

A1627418 at 01:52, 23 October 2015

2015-10-23T01:52:09Z

A1627418 at 01:32, 23 October 2015

2015-10-23T01:32:08Z

A1627418: /* Project Management */

2015-10-23T01:29:48Z

‎Project Management

A1627418 at 01:27, 23 October 2015

2015-10-23T01:27:05Z

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 The final of three algorithms developed uses a blob detection method.  Firstly, the image data is converted to binary values. Pixel intensities with a brightness above a given threshold are given a value of one, dark pixels are set to zero. This decreases the size of the data so that it can be stored on the processor, allowing two passes across the data set.   The algorithm identifies all the blobs in an image and then compares the size of each with the expected size of the sun which is adjustable and has been determined experimentally.  If a blob around the size of the sun is detected, the average position of these pixels exclusively will be used to approximate the centre of the sun.
-This algorithm has been trialled in MATLAB with some promising results.  Figure 27 and Figure 28 compare the new algorithm implemented in MATLAB with the initial image processing algorithm using a photo of the sun, taken by the sun sensor flight model.  Again, in Figure 27, the red pixels indicate the pixels that are above the threshold, and the small blue crosshair represents the approximation of the centroid pixel.  In Figure 28, the white pixels indicate blobs detected that are above the threshold value, the green pixels indicate the blob that is assumed to be the sun and the red cross shows the new approximation of the centroid.
+This algorithm has been trialled in MATLAB with some promising results.  The images below compare the new algorithm implemented in MATLAB with the initial image processing algorithm using a photo of the sun, taken by the sun sensor flight model.  Again, in Figure 27, the red pixels indicate the pixels that are above the threshold, and the small blue crosshair represents the approximation of the centroid pixel.  In the revised algorithm image, the white pixels indicate blobs detected that are above the threshold value, the green pixels indicate the blob that is assumed to be the sun and the red cross shows the new approximation of the centroid.
-Figure 27 - Image of the Sun Taken by the Sun Sensor, Overlaid is the Result of the Initial Algorithm
+Image of the Sun Taken by the Sun Sensor, Overlaid is the Result of the Initial Algorithm
-Figure 28 - Same Image of the Sun Processed Using the Revised Algorithm in MATLAB
+[[File:Final_algorithm_result.png]]
 It is clear that the revised algorithm boasts a greater accuracy in the presence of reflections has the ability to distinguish between the sun and other bright elements based on size.  However, as a trade-off the revised algorithm requires a two pass process and a reasonable amount of data storage. This introduces error due to processing delays.
 == '''''Conclusions''''' ==

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 ===== Project Outcome =====
 The project successfully saw the development of the three software aspects required for the successful integration of the sun sensor into the satellite.  Namely: the external communications interface; internal communications; and the centroid calculation algorithm.
-In Section 3.3 the development of the external communications interface of the sun sensor was described.  It now provides a swift transfer of data through the use of interrupt flags and routines.  As such, error due to the delay between image reception and the request of the sun location from the master device is minimised.
+The development of the external communications interface of the sun sensor was described.  It now provides a swift transfer of data through the use of interrupt flags and routines.  As such, error due to the delay between image reception and the request of the sun location from the master device is minimised.
-Section 3.2 described the process behind coding, testing and debugging the internal communications on-board the sun sensor.  This provided functionalities including: the ability to adjust camera settings; and port image data from the camera to the processor.
+The process behind coding, testing and debugging the internal communications on-board the sun sensor was undertaken.  This provided functionalities including: the ability to adjust camera settings; and port image data from the camera to the processor.
-Section 4 exemplifies several revisions of a sun sensing algorithm which explored the benefits and cons of various methodologies.  An accurate method that uses a blob detection algorithm followed by averaging has been selected and demonstrated in MATLAB.
+Several revisions of a sun sensing algorithm which explored the benefits and cons of various methodologies.  An accurate method that uses a blob detection algorithm followed by averaging has been selected and demonstrated in MATLAB.
 Along the way, knowledge and skills were also gained through unexpected complications within the project.  Namely: solving the problem of overexposure and the protection of the image sensor using solar safety film; and debugging electronic signals and communication protocols using an oscilloscope and logic analysis tools.

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 The test setup from the external I2C communications test was revised.  The image sensor transfers image data to the buffer, the processor receives image data line by line, and sends the lines to the mbed development board through the external I2C link.  The mbed device stores the image data in a text file as it is received.  After the transmission is complete, a program coded in Java interprets the image data, converts it to a PNG format and saves the image.
-Figure 18 - Images Taken in RGB (left) and YUV (right) Formats after Timing Issues Were Resolved
+The Images Taken in RGB (left) and YUV (right) Formats after Timing Issues Were Resolved
 Images taken after the timing issues were resolved produced expected output.  Figure 18 shows two images of a flashlight in the lab in both RGB and only intensity values from the YUV image format.  Note that the red pixels in the YUV image are overlayed in Java and represent the brightest pixels in the image.  This was implemented to determine the suitability of the image for processing purposes.  The YUV format was selected for use in the image processing due to its simple pixel information structure.

@@ Line 362: / Line 362: @@
 The test setup from the external I2C communications test was revised.  The image sensor transfers image data to the buffer, the processor receives image data line by line, and sends the lines to the mbed development board through the external I2C link.  The mbed device stores the image data in a text file as it is received.  After the transmission is complete, a program coded in Java interprets the image data, converts it to a PNG format and saves the image.
 Figure 18 - Images Taken in RGB (left) and YUV (right) Formats after Timing Issues Were Resolved
 Images taken after the timing issues were resolved produced expected output.  Figure 18 shows two images of a flashlight in the lab in both RGB and only intensity values from the YUV image format.  Note that the red pixels in the YUV image are overlayed in Java and represent the brightest pixels in the image.  This was implemented to determine the suitability of the image for processing purposes.  The YUV format was selected for use in the image processing due to its simple pixel information structure.
 ===== Sun Centroid Calculation Algorithm =====

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 A state machine has been designed to provide a more secure mechanism for handling the interrupts and transfer processes.
-Figure 11 - I2C Interrupt Handler State Machine
+[[File:state_machine.png]]
-Figure 11 shows the states of I2C interrupt handler.  Changes between states are dependent on the I2C interrupt flags that are set by hardware.  For example, from the idle state, if the flag that indicates the slave being addressed is set high, then the state machine will reset required flags and proceed through to the start state.
 The state machine manages the master’s requests to send or receive any number of bytes.  If an error is detected, the state machine clears all flags and returns to the idle state ensuring that the slave device does not lock up the bus.

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 The test setup validated the correct operation of the polled external communication ability of the sun sensor.  The outputs on the PC terminal, the binary pattern on the LEDs, and the oscilloscope monitoring the transmission lines, verified that the sun sensor was successfully transferring valid data.
-−
-Figure 10 - External I2C Communications Test Setup
+[[File:Ext_comms_test.png]]
-Figure 10 shows the operating test setup used to verify the correct operation of the polled I2C implementation.  The mbed development board in the bottom left hand corner is displaying the values provided by the sun sensor board in the centre.  The oscilloscope is monitoring the I2C clock (yellow) and data (blue) lines between the devices.
+External I2C Communications Test Setup
 ====== Further Developments ======
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 Figure 11 shows the states of I2C interrupt handler.  Changes between states are dependent on the I2C interrupt flags that are set by hardware.  For example, from the idle state, if the flag that indicates the slave being addressed is set high, then the state machine will reset required flags and proceed through to the start state.
 The state machine manages the master’s requests to send or receive any number of bytes.  If an error is detected, the state machine clears all flags and returns to the idle state ensuring that the slave device does not lock up the bus.
 ===== Internal Communications Development=====

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 Software Implementation of Sun Sensor Algorithm
-The sun sensor software will be based on an algorithm designed by a previous student in a former year of the project life [12].  From both a user and processor perspective, the algorithm is purposefully simple.  Firstly the image is grey-scaled, and the relative intensity values in each row and column are summed.  These sums are used to draw a virtual 'box' around the brightest area in the picture.  The position of the box centre is then used to calculate the directional vector pointing toward the sun.  Figure 2 provides a visual representation of this process.
+The sun sensor software will be based on an algorithm designed by a previous student in a former year of the project life.  From both a user and processor perspective, the algorithm is purposefully simple.  Firstly the image is grey-scaled, and the relative intensity values in each row and column are summed.  These sums are used to draw a virtual 'box' around the brightest area in the picture.  The position of the box centre is then used to calculate the directional vector pointing toward the sun.  Figure 2 provides a visual representation of this process.
 Working operation of the algorithm has been verified in a Java implementation using still images on a PC.  The future challenge in this task lies in the embedded nature of the software and communication with both the CMOS sensor and the on-board-computer.  There will also have to be an inquiry into whether calibration is required for the use of the fish eye lens.
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 == '''''Results''''' ==
 == '''''Conclusions''''' ==
 == '''''References''''' ==
 <references/>

← Older revision		Revision as of 01:32, 23 October 2015
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	==== Autonomous ACDS ====		==== Autonomous ACDS ====
		+
		+	== '''''Results''''' ==

	== '''''Conclusions''''' ==		== '''''Conclusions''''' ==

← Older revision		Revision as of 01:29, 23 October 2015
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	==== Autonomous ACDS ====		==== Autonomous ACDS ====
−
−	~~== '''''Project Management''''' ==~~
−
−	~~=== ''Budget'' ===~~
−
−	~~=== ''Risk Analysis'' ===~~
−
−	~~=== ''WBS'' ===~~
−
−	~~=== ''Gantt Chart'' ===~~

	== '''''Conclusions''''' ==		== '''''Conclusions''''' ==

← Older revision		Revision as of 01:27, 23 October 2015
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−	~~Cubesats~~ are ~~da bomb~~	+	The development of Cube-Satellites is providing cheaper and easier access to space for purposes of exploration and experimentation. LAUNCHBOX and South Australian universities are undertaking the development of a Cube-Satellite that will be fit for use in the creation of a wireless ad-hoc network in space as part of the QB50 project.
		+
		+	This wiki covers the development of several aspects of a cube satellite. An On-Board Computer (OBC), Electrical Power System (EPS), Sun Centroid Sensor and Earth Horizon Detection Sensor.

	== '''''Project Information''''' ==		== '''''Project Information''''' ==