Changes between Version 45 and Version 46 of Old/Dailyupdates


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Timestamp:
Jul 6, 2007, 9:51:59 PM (17 years ago)
Author:
aniket
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  • Old/Dailyupdates

    v45 v46  
    66[wiki:robotmobilityweek4: Week4]
    77   
    8 == 7/3/07 - Day 21 ==
     8== 7/2/07 - Day 21 ==
    99
    1010We are continuing to work on our algorithms to improve their speed and reliability. We have some time on the grid reserved for tomorrow morning as well as 2pm on Thursday and Friday.
    … …  
    1414There are many useful tools in the packages ''numpy'', ''scipy'', and ''matplotlib''. We can generate high quality plots directly from python, which is easing the data analysis process.
    1515
    16 == 7/2/07 - Day 22 ==
     16== 7/3/07 - Day 22 ==
    1717
    1818We have begun working on a new grand solution to the access point locating challenge. We are working on an intellegent python program which combines different types of regression analysis to locate the AP.
    … …  
    2828
    2929Another fundamental difference between this project and previous algorithms is that we are making more careful decisions about data structures. I am trying to use numpy's arrays as much as possible. All of the data collected, since it all needs to be stored and recalled, will be held in a single array. Functions are in place to add new data points to this array and extract from it lists of X,Y, and S values.
     30
     31== 7/5/07 - day 23 ==
     32
     33We are under way coding our ultimate solution to the access point problem. The first thing we've begun to do is assemble different python modules for different purposes, keeping the main code clean and readable. We have a module that handles the data, a module tha handles plotting, and a module that takes care of statistical analysis.
     34
     35
     36== 7/6/07 - day 24 ==
     37
     38The data we are gathering is very reluctant to fit the shapes we are trying to fit. The once-considered-reliable algorithm "bigtri.py" is producing erratic and inconsistant results. Using a least squares method to fit the data to a cone shape is frustratingly innacurate.
     39
     40I've written some code, "snake.py", which snakes along a hallway taking measurements. The computer is connected to a LinkSys router at the other end of the hall. I tried fitting the data to a cone with known slope and z-value at the apex. The leastsq procedure was trying to solve for the x,y location of the cone's apex (the Access Point), and the result was far from accurate. I plotted the gathered data against the expected cone in matlab only to find that the data contained distinctly higher values than the cone I was hoping it would fit to.
     41
     42The cone I was hoping to fit was the equation: z = a * sqrt((x-x0)^2+(y-y0)^2) + z0, where a is the cone slope and (x0,y0,z0) is the location of the apex. In my test run, with all of a,x0,y0,z0 known, all of the experimental data had much higher z values than the anticipated cone. To compensate, I raised the z0 value from 26.17 to 40, which looked like a much more appropriate fit. However, the leastsquares method still fails to locate the apex of this cone.
     43
     44In order to determine the shape, we had one robot wander around orbit (we had some grid time today) taking measurements. The data is difficult to interpret, but I have begun to do some preliminary curve fitting to it. My hope is to be able to crack the code and be able to reliably identify the location of the access point from a random sampling of the large set of data. So far the prospects are dim - the data is very noisy.
     45