Projects:2018s1-122 NI Autonomous Robotics Competition - Revision history

A1719425: /* Localisation */

2018-10-19T04:10:19Z

‎Localisation

A1650078: /* Smooth Motion */

2018-10-19T04:00:24Z

‎Smooth Motion

A1650078: /* Hough Transform */

2018-10-19T03:59:57Z

‎Hough Transform

A1719425: /* Robot Frame */

2018-10-19T03:34:45Z

‎Robot Frame

A1719425: /* NI LabVIEW 2017 Programming Environment */

2018-10-19T03:33:37Z

‎NI LabVIEW 2017 Programming Environment

A1650078: /* Hough Transform */

2018-10-19T03:29:02Z

‎Hough Transform

A1650078: /* Hough Transform */

2018-10-19T03:26:13Z

‎Hough Transform

A1719425: /* NI LabVIEW 2017 Programming Environment */

2018-10-19T03:25:51Z

‎NI LabVIEW 2017 Programming Environment

A1650078: /* Hough Transform */

2018-10-19T03:25:39Z

‎Hough Transform

A1719425: /* NI MyRIO-1900 Real-Time Embedded Evaluation Board */

2018-10-19T03:25:30Z

‎NI MyRIO-1900 Real-Time Embedded Evaluation Board

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 [[File:EncoderFormulas.png|300px|center|Encoder Navigation]]
 <br clear="all" />
 == Object Detection and Avoidance ==

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 === Dynamic Window ===
 While Dynamic Window is typically used as a collision avoidance strategy for mobile robots, its main function in this case was to produce smooth acceleration and braking profiles, as well as motion planning for cornering in arcs. This implementation takes into account the maximum linear and rotational velocity specified by the control system, and uses an array of different velocity profiles to determine the most optimal route to a target point, by scoring each profile against user-defined desired movement parameters including path velocity, heading to target, arc length and change in heading over the course of the arc. The most optimal path that won't overshoot the target point is then represented by the its component linear and rotational velocities and passed to the motor control loop to produce the correct wheel speeds for that path.
 == Achievements ==

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 The Hough Transform is a voting algorithm for finding the straight lines in an image. To detect lines of pink tape, for example, all pink pixels in the image are passed to the Hough Transform algorithm. For every possible straight line, the pink pixels on that line are counted up. At the end, the lines which pass through the tape in the camera image will have the highest number of pink pixels.
-The Hough Transform is very memory intensive. It requires reading and writing to an array of counters millions of times (78,643,200 times to be precise). Additionally, the transform must be repeated many times each second. The main CPU on the myRIO is not capable of accessing memory this quickly. The FPGA however is ideal for the Hough Transform. It has it's own very fast internal memory. In our implementation, even the low performance FPGA on the myRIO can vote for 1.3 ''billion'' lines per second. This is much faster than the memory on a desktop PC.
+This process is very memory intensive. It requires reading and writing to an array of counters millions of times (78,643,200 times to be precise). Additionally, the transform must be repeated many times each second. The main CPU on the myRIO is not capable of accessing memory this quickly. The FPGA however is ideal for the Hough Transform. It has it's own very fast internal memory. In our implementation, even the low performance FPGA on the myRIO can vote for 1.3 ''billion'' lines per second. This is much faster than the memory on a desktop PC.
 === Determining Image Processing Pipeline in Matlab ===

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 * Laser cut acrylic chassis designed in Autodesk AutoCAD
 * Curved aluminium sensor mounting bar
 [[File:RoboNIARC Construction.jpeg|500px|]]

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 * System-design platform and graphical development environment provided by NI
 * Extensive library of MyRIO toolkits, including FPGA, sensor I/O and data processing tools
-* Real-time simulation of virtual instruments to predict real-world robot behaviour
+* Real-time graphical visualisation of code execution
 MyRIO processor and FPGA were programmed using LabVIEW 2017, a graphical programming environment. Additional LabVIEW modules were used to process the received sensor information, such as the 'Vision Development Module' and 'Control Design and Simulation Module'.

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 === Hough Transform ===
-The Hough Transform is an voting algorithm for finding the straight lines in an image. To detect lines of pink tape, for example, all pink pixels in the image are passed to the Hough Transform algorithm. For every possible straight line, the pink pixels on that line are counted up. At the end, the lines which pass through the tape in the camera image will have the highest number of pink pixels.
+The Hough Transform is a voting algorithm for finding the straight lines in an image. To detect lines of pink tape, for example, all pink pixels in the image are passed to the Hough Transform algorithm. For every possible straight line, the pink pixels on that line are counted up. At the end, the lines which pass through the tape in the camera image will have the highest number of pink pixels.
 The Hough Transform is very memory intensive. It requires reading and writing to an array of counters millions of times (78,643,200 times to be precise). Additionally, the transform must be repeated many times each second. The main CPU on the myRIO is not capable of accessing memory this quickly. The FPGA however is ideal for the Hough Transform. It has it's own very fast internal memory. In our implementation, even the low performance FPGA on the myRIO can vote for 1.3 ''billion'' lines per second. This is much faster than the memory on a desktop PC.

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 === NI LabVIEW 2017 Programming Environment ===
 * System-design platform and graphical development environment provided by NI
-* Expansive library of MyRIO toolkits, including FPGA, sensor I/O and data processing tools
+* Extensive library of MyRIO toolkits, including FPGA, sensor I/O and data processing tools
 * Real-time simulation of virtual instruments to predict real-world robot behaviour
 * Graphical visualisation of code execution

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 === NI MyRIO-1900 Real-Time Embedded Evaluation Board ===
 * Xilinx Zynq 7010 FPGA - parallel sensor data acquisition and webcam image processing
-* ARM microprocessor – computation, code execution and decision making.
+* ARM microprocessor – computation, code execution and decision making
 [[File:myrio.jpg|300px|left|NI MyRIO - 1900]] <br />