This file was opened on Fri, Oct 09 2015. It is currently 9:44:08 PM.

Introduction to the IMU Sensor

The IMU sensor contains a variety of sensors and is therefore crucial to having a robot… [continue]

Imported Libraries

Here are the libraries that were installed for this r program. The “data. table”" library helps us organize our data, and the “tidyr” and “dplyr” libaries help us process and analyze our data more efficiently.

library(data.table)
library(tidyr)
library(dplyr)
## 
## Attaching package: 'dplyr'
## 
## The following objects are masked from 'package:data.table':
## 
##     between, last
## 
## The following objects are masked from 'package:stats':
## 
##     filter, lag
## 
## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union

Renaming Sensor Names

Here, we decided to rename our sensor names as well as the “Time”" variable for convenience during the analysis of the data.

fixSensorNames = function(zte, prefixName) {
  setnames(zte, "Euler H", paste0(prefixName, "eulerh"))
  setnames(zte, "Euler P", paste0(prefixName, "eulerp"))
  setnames(zte, "Euler R", paste0(prefixName, "eulerr"))
  setnames(zte, "Time (ms)", paste0(prefixName, "time"))
  
   setnames(zte, "Linear Acceleration X", paste0(prefixName, "accelx"))
  setnames(zte, "Linear Acceleration Y", paste0(prefixName, "accely"))
  setnames(zte, "Linear Acceleration Z", paste0(prefixName, "accelz"))
}

Reading the Data from Excel

The r code here reads the excel data file and converrts the time to 100ms. The code here also gets the sensor data and the time ready to be joined into a data table for analysis.

setwd("C:/Users/Simon/Documents/R/Data")
imu = fread("imu_data.csv") 
fixSensorNames(imu, "i.")# convert epoch time to 100ms, prepare to join

IMU Data

Before proceeeding to further analysis, we first decided to get a summary of the data in order to get a rough idea of what our data table is like.

summary(imu)
##      i.time         i.eulerh        i.eulerp           i.eulerr     
##  Min.   :    0   Min.   :  0.0   Min.   :-153.000   Min.   :-81.00  
##  1st Qu.: 8478   1st Qu.:197.0   1st Qu.: -67.000   1st Qu.:-48.00  
##  Median :16955   Median :241.0   Median :   0.000   Median :-23.00  
##  Mean   :16955   Mean   :225.3   Mean   :   1.835   Mean   :-24.87  
##  3rd Qu.:25433   3rd Qu.:291.0   3rd Qu.:  86.000   3rd Qu.:  2.00  
##  Max.   :33910   Max.   :359.0   Max.   :  87.000   Max.   : 14.00  
##     i.accelx           i.accely          i.accelz        Quaternion W  
##  Min.   :-10.0000   Min.   :-51.000   Min.   :-28.000   Min.   :  0.0  
##  1st Qu.: -1.0000   1st Qu.: -9.000   1st Qu.: -4.000   1st Qu.:407.0  
##  Median :  0.0000   Median :  0.000   Median : -2.000   Median :711.0  
##  Mean   :  0.1424   Mean   : -1.498   Mean   : -1.331   Mean   :647.7  
##  3rd Qu.:  1.0000   3rd Qu.:  6.000   3rd Qu.:  1.000   3rd Qu.:956.0  
##  Max.   : 13.0000   Max.   : 47.000   Max.   : 26.000   Max.   :991.0  
##   Quaternion X   Quaternion Y    Quaternion Z   Max Read Interval
##  Min.   :-949   Min.   :  0.0   Min.   :-31.0   Min.   : 4.169   
##  1st Qu.:-885   1st Qu.:336.0   1st Qu.:177.8   1st Qu.:30.315   
##  Median :-573   Median :755.5   Median :650.0   Median :30.315   
##  Mean   :-521   Mean   :646.7   Mean   :547.6   Mean   :29.659   
##  3rd Qu.:-232   3rd Qu.:919.0   3rd Qu.:863.0   3rd Qu.:30.315   
##  Max.   : 134   Max.   :970.0   Max.   :970.0   Max.   :30.914   
##  Average Read Interval
##  Min.   : 0.008143    
##  1st Qu.:10.454268    
##  Median :14.033233    
##  Mean   :12.375019    
##  3rd Qu.:15.573770    
##  Max.   :15.877986

Next, we took the standard deviation and mean of the data.

mean(imu$i.eulerh)
## [1] 225.2624
sd(imu$i.eulerh)
## [1] 99.13568
mean(imu$i.eulerp)
## [1] 1.834611
sd(imu$i.eulerp)
## [1] 74.24259
mean(imu$i.eulerr)
## [1] -24.86704
sd(imu$i.eulerr)
## [1] 29.33657
mean(imu$i.accelx)
## [1] 0.1423939
sd(imu$i.accelx)
## [1] 2.40381
mean(imu$i.accely)
## [1] -1.497642
sd(imu$i.accely)
## [1] 18.18913
mean(imu$i.accelz)
## [1] -1.331368
sd(imu$i.accelz)
## [1] 6.135536

IMU Graph

Below is the graph of the IMU data. [describe data]

Conclusion

Based on… [write this]