S16: Helios - Revision history

Proj user8: /* Software Design */

2016-05-24T13:58:46Z

‎Software Design

Proj user8: /* Color Detection */

2016-05-24T05:20:25Z

‎Color Detection

Proj user8: /* References Used */

2016-05-24T05:18:04Z

‎References Used

Proj user8: /* Conclusion */

2016-05-24T02:35:23Z

‎Conclusion

Proj user8: /* Raspberry Pi */

2016-05-24T02:32:28Z

‎Raspberry Pi

Proj user8: /* Interface with SJOne Master Board */

2016-05-24T02:29:44Z

‎Interface with SJOne Master Board

Proj user8: /* Interface with SJOne Slave Board */

2016-05-24T02:29:16Z

‎Interface with SJOne Slave Board

Proj user8: /* Interface with SJOne Master Board */

2016-05-24T02:25:38Z

‎Interface with SJOne Master Board

Proj user8: /* Interface with SJOne Master Board */

2016-05-24T02:14:34Z

‎Interface with SJOne Master Board

Proj user8: /* Interface with SJOne Master Board */

2016-05-24T02:10:19Z

‎Interface with SJOne Master Board

@@ Line 466: / Line 466: @@
 === Software Design ===
 ==== Assembly line Mechanism ====
 [[File:CMPE_244_S16_Helios_SJOneMaster.png|center|700px|thumb|Master SJOne board Flow Sequence]]

@@ Line 511: / Line 511: @@
 As shown in the fig. we can change the minimum values of H, S, and V in such a manner that only the desired color will remain as a whitespace and rest of the image should be dark. Once the minimum and maximum values are determined we can lock down these values with inRange() function to get the thresholded image.
-    int createTrackbar(const string& trackbar name, const string& winname, int* value, int count, TrackbarCallback)  is the library function which was used to create the trackbars.
+    int createTrackbar(const string& trackbar name, const string& winname, int* value, int count, TrackbarCallback)
 [[File:CMPE_244_S16_Helios_Trackbars.JPG|center|500px|thumb|RGB Planes]]

@@ Line 619: / Line 619: @@
 *[https://www.raspberrypi.org/ Raspberry Pi]
 *[http://opencv.org/ OpenCV]
 === Appendix ===
 *[http://opencv.org/quickstart.html OpenCV cross compilation]
 *[http://docs.opencv.org/2.4/modules/refman.html OpenCV API references]

@@ Line 600: / Line 600: @@
 == Conclusion ==
-The learning experience our team wanted to have was to learn about things we had not done before. This is reflected in the major components in the project, such as the use of image processing. This further led to the realization that SJOne cannot be used for image processing and hence we had to to look for other resources. The use of an embedded linux computer enhanced our understanding of an RTOS. The use of two different Operating Systems: FreeRTOS and Raspbian Jessie helped us in understanding the different use cases for them and how the software complements the hardware.
+The learning experience our team wanted to have was, to learn about things we had not done before. This is reflected in the major components in the project, such as the use of image processing. This further led to the realization that SJOne cannot be used for image processing and hence we had to to look for other resources. The use of an embedded linux computer enhanced our understanding of an RTOS. The use of two different Operating Systems: FreeRTOS and Raspbian Jessie helped us in understanding the different use cases for them and how the software complements the hardware.
 Another takeaway from this project is the build. Building the conveyor system was challenging and needed a lot of original thinking. Cross compiling of OpenCV was another major part of this project and it helped us understand how libraries and compilers work together and help in writing programs easily. This aspect of programming is often neglected in application programming and this project gave us a deep insight into this.In conclusion, it can be said that the project was a success and it has been successful in making us understand Embedded Software better.

@@ Line 234: / Line 234: @@
 #With an internet connectivity adding dependencies was easy using “sudo apt-get install”
 After searching the internet for methods to compile the libraries we came across [https://www.raspberrypi.org/forums/viewtopic.php?f=32&t=122555 this script] to install the libraries and its dependencies.
 ==== Conveyor Belt ====

@@ Line 377: / Line 377: @@
 *IR sensor: The IR sensor detects the presence of an object. This is needed because the camera can detect only the valid colors, but there is no way for the camera to know whether there is an object that is of the wrong color or if there are no objects.
 *Servo motor for rejection: The servo motor requires has three pins: VCC, GND and PWM signal. The PWM signal is provided at port 2 pin 1. This servo motor is responsible for rejecting any object that is not blue or green in color. The decision to swing the servo motor arm is based on the information received on the I2C interface and the IR sensor input.
 {| class="wikitable"
 |-

@@ Line 424: / Line 424: @@
 *IR sensor to detect object: The IR sensor detects the presence of an object. This is needed because the camera can detect only the valid colors, but there is no way for the camera to know whether there is an object that is of the wrong color or if there are no objects.
 *Servo motor for sorting: The servo motor connected to the slave is responsible for sorting the green object, but allow the blue object to pass through. The decision to swing the servo motor arm is based on the information received on the Nordic wireless interface and the IR sensor input.
 === Software Design ===

@@ Line 379: / Line 379: @@
 {| class="wikitable"
 |-
 ! scope="col"| SJ One Pin
 ! scope="col"| Peripheral Name
@@ Line 385: / Line 386: @@
 |-
-! scope="row"
+! scope="row"| 1
 | SDA
 | RaspberryPi
@@ Line 391: / Line 392: @@
 |SDA pin for I2C communication
 |-
 |}