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drexel_darwin_slam [2016/11/06 12:58] – [Implementation] dwallacedrexel_darwin_slam [2016/11/06 19:42] (current) dwallace
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 I designed the robot such that the Ultrasonic Sensor is along the axle of the motor driving the wheels. I designed the robot such that the Ultrasonic Sensor is along the axle of the motor driving the wheels.
  
-{{dylanw:2013-03-30 19.02.55.jpg}}\\  +{{dylanw:2013-03-30_19.02.55.jpg}}\\  
-{{dylanw:2013-03-30 19.02.06.jpg}}\\ +{{dylanw:2013-03-30_19.02.06.jpg}}\\ 
  
 Picture of the experimental setup. Picture of the experimental setup.
  
-{{dylanw:2013-04-03 08.01.01.jpg}}\\ +{{dylanw:2013-04-03_08.01.01.jpg}}\\ 
  
 This is the "nxc" code for the whole procedure. This is the "nxc" code for the whole procedure.
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 This is the result on Matlab. The red line represents the experimental boundary, the green line represents the route taken by the robot WITHOUT corrections, and the blue dots represent the detected obstacles at the respective part of the route. This is the result on Matlab. The red line represents the experimental boundary, the green line represents the route taken by the robot WITHOUT corrections, and the blue dots represent the detected obstacles at the respective part of the route.
  
-{{dylanw:SLAM1.jpg}}\\ +{{dylanw:slam1.jpg}}\\ 
  
 This is a video of the experiment. This is a video of the experiment.
  
-{{#ev:youtube|SDNhBZ4B8Mk}}\\ +{{youtube>SDNhBZ4B8Mk?large}}\\ 
  
 Thoughts: Thoughts:
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 his is the first trial on capturing landmark on a 180 degrees sweep of the front surrounding, and writing the values into a file. his is the first trial on capturing landmark on a 180 degrees sweep of the front surrounding, and writing the values into a file.
  
-{{#ev:youtube|D-EGa5qmdC4}}\\ +{{youtube>D-EGa5qmdC4?large}}\\ 
  
 This is the nxc code for: This is the nxc code for:
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 Below shows the collected figures from the program. Below shows the collected figures from the program.
  
-{{dylanw:coordinatesNAreas.jpg}}\\ +{{dylanw:coordinatesnareas.jpg}}\\ 
  
 Explanation: Explanation:
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 This is specially designed as such to eliminated the need for transformation of the position of the sensor to the wheels, hence the vehicle can be modeled as a point in space easily. This is specially designed as such to eliminated the need for transformation of the position of the sensor to the wheels, hence the vehicle can be modeled as a point in space easily.
  
-{{dylanw:NXTfinalDesign1.jpg}}\\  +{{dylanw:NXTfinalDesign1.jpg}}{{dylanw:NXTfinalDesign2.jpg}}\\ 
-{{dylanw:NXTfinalDesign2.jpg}}\\ +
  
 The robot moves in a straight line for 5 steps. The robot moves in a straight line for 5 steps.
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 Here is the video. (I changed the white obstacle to black) Here is the video. (I changed the white obstacle to black)
  
-{{#ev:youtube|Q4xNY9fbCFA}}+{{youtube>Q4xNY9fbCFA?large}}\\ 
  
 The recorded files are displayed below with slight explanations. These files are recorded in a different trial as the one recorded in the video above. The recorded files are displayed below with slight explanations. These files are recorded in a different trial as the one recorded in the video above.
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 {{dylanw:blue.jpg}}\\  {{dylanw:blue.jpg}}\\ 
 +
   * If a true blob is not detected in one scan, that is there is no blue object in the a scan, default value of 255 is written into a line in the file.   * If a true blob is not detected in one scan, that is there is no blue object in the a scan, default value of 255 is written into a line in the file.
   * If a true blob is detected, the angle and the distance at which it is detected is recorded.   * If a true blob is detected, the angle and the distance at which it is detected is recorded.
   * If more than one blob is detected, the pair of angle and distance values are recorded separately from the other pairs in a line.   * If more than one blob is detected, the pair of angle and distance values are recorded separately from the other pairs in a line.
  
-  * *^white.dat**+  * **white.dat**
  
 {{dylanw:white.jpg}}\\  {{dylanw:white.jpg}}\\ 
 +
   * Same explanation with the blue blob detection above.   * Same explanation with the blue blob detection above.
   * Note that a black object is used instead.   * Note that a black object is used instead.
  
-  * ^*distFwdAngle.dat**+  * **distFwdAngle.dat**
  
 {{dylanw:distFwdAng.jpg}}\\  {{dylanw:distFwdAng.jpg}}\\ 
 +
   * Each line represent the state of the robot at each step of its journey.   * Each line represent the state of the robot at each step of its journey.
   * In each line, the value before the space is the change in orientation of the robot, while the value after is a state function of whether the robot move forward or not.   * In each line, the value before the space is the change in orientation of the robot, while the value after is a state function of whether the robot move forward or not.
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 Here are the results of the data collected in the experiment shown in the video. Here are the results of the data collected in the experiment shown in the video.
  
-{{dylanw:bluedat.jpg}}\\  +{{dylanw:bluedat.jpg}}{{dylanw:whitedat.jpg}}\\ 
-{{dylanw:whitedat.jpg}}\\ +
  
-{{#ev:youtube|fN0vzS6yzbQ}}\\ +{{youtube>fN0vzS6yzbQ?large}}\\ 
  
 == Trial 4 == == Trial 4 ==
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 In addition, I will use a white background instead as the capturing of blobs based on the designated colormap is not very effective. This picture shows the blobs detected when the same colormap is used to capture images at different angles using a green background. Using a white background and black landmarks might make the difference since they are the extremes of the color spectrum. In addition, I will use a white background instead as the capturing of blobs based on the designated colormap is not very effective. This picture shows the blobs detected when the same colormap is used to capture images at different angles using a green background. Using a white background and black landmarks might make the difference since they are the extremes of the color spectrum.
  
-{{dylanw:badOverlapping.jpg}}\\ +{{dylanw:badoverlapping.jpg}}\\ 
  
 The final experimental set up is shown in the picture below. The final experimental set up is shown in the picture below.
  
-{{dylanw:trial4ExpSetup.jpg}}\\ +{{dylanw:trial4expsetup.jpg}}\\ 
  
 The nxc code is show below. The nxc code is show below.
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 This is the full video at normal speed. This is the full video at normal speed.
  
-{{#ev:youtube|YjQGph-r7jo}}\\ +{{youtube>YjQGph-r7jo?large}}\\ 
  
 This is a compilation of the 'blob' and 'LMdist' data collected. This is a compilation of the 'blob' and 'LMdist' data collected.
  
-{{dylanw:retrievedData.jpg}}\\ +{{dylanw:retrieveddata.jpg}}\\ 
  
   * Each line represented the 29 data of all the scans done at each move step.   * Each line represented the 29 data of all the scans done at each move step.
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 I tested out the algorithm on another experimental setup as shown below. I tested out the algorithm on another experimental setup as shown below.
  
-{{dylanw:trial5expSetup.jpg}}\\ +{{dylanw:trial5expsetup.jpg}}\\ 
  
 With an adjustment to the minimum distance threshold between landmarks to be classified as the same landmark, the results are show below. With an adjustment to the minimum distance threshold between landmarks to be classified as the same landmark, the results are show below.
drexel_darwin_slam.txt · Last modified: 2016/11/06 19:42 by dwallace