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Feasibility  of  implemenEng  a  laser-­‐distancing  system  for  an  unmanned  aerial  vehicle  

Junyi  Dai;  Supervised  by  Dominic  Robillard,  Charles  Blouin,  and  Eric  Lanteigne    Department  of  Mechanical  Engineering,  University  of  Okawa  

Junyi  Dai  Mechanical  Engineering  Student    Email:  jdai013@uokawa.ca  Phone:  613-­‐816-­‐1177  

Contact  1.  Dai,  Junyi  (Photographer).  (2014,  November  19th).  Sonar,  camera,  and  laser  set-­‐up.  2.  Dai,  Junyi  (Photographer).  (2014,  December  28th).  Laser  dot  through  a  camera-­‐lens  at  close  range  and  at  far-­‐range.  3.  Dai,  Junyi  (Photographer)  with  permission  from  Tyto  Robo?cs.  (2015,  January  30th).  Small  helicopter  UAV.  4.  Danko,  Todd  (Ar?st).  (2009,  August  25th).  Laser  Ranger  Drawing.  Retrieved  from  hkp://www.codeproject.com/KB/cs/

range_finder/laser-­‐range-­‐finder-­‐1.gif  5.  Wiora,  Georg  (Ar?st).  (2005,  October  5th).  Principle  of  a  sonar  or  radar  distance  measurement.  Retrieved  from  hkp://                          

www.kerrywong.com/blog/wp-­‐content/uploads/2011/01/2000px-­‐Sonar_Principle_EN.svg_.png  

References  

One   of   the   fundamental   parameters   during   the   flight   of   an  unmanned  aerial  vehicle  (UAV)  is  the  al?tude  at  which  it  is  flying  at.  One  method   is   to  use   sonar   sensors,  which   emit   a   pulse  of   sound  and  uses  the  ?me-­‐of-­‐flight  of  the  echo  to  calculate  the  distance.  It  is  however   unreliable   due   to   slow   refresh   rates   and   erroneous  readings  caused  by  interfering  echoes.    This   research   project   aims   to   determine   the   feasibility   of  implemen?ng  a  laser-­‐distancing  system  for  a  small  UAV  in  order  to  determine   its   al?tude.   It   is   known   that   the   distance   between   a  projected   laser  dot  on  a   camera   focal  plane  and   the   center  of   the  focal  plane  can  be  related  through  triangula?on.  This  can  be  used  to  find   the  distance   to   the  surface   that   the   laser  was  projected  onto.  The   results   from   this   research   project   will   provide   a   proof-­‐of-­‐concept   for   the   laser-­‐distancing   system,   which   can   poten?ally  replace  current  unreliable  sonar  distancing  implementa?ons.  

IntroducEon  

The   measured   experimental   distances   were   accurate   when  compared   to   the   actual   distances.   The   percent   error   ranged   from  3.76%  to  9.97%,  and  the  average  percent  error  was  5.46%  (see  Table  1  and  Figure  3).  As  seen  in  Figure  2,  when  the  camera  and  laser  set-­‐up  was   farther   away   from   the  wall   along   the   same   axis,   the   laser  appeared  closer  to  the  center  of  the  focal  plane.  Similarly,  the  laser  would  appear  farther  away  from  the  center  of  the  focal  plane  as  the  camera  and  laser  set-­‐up  is  moved  closer  to  the  wall.  

To  determine  the  feasibility  of  using  this  laser  system,  MATLAB  will  be  used  to  develop  a  model  to  test  the  system.  A  webcam  will  send  real-­‐?me   video   of   the   laser   projec?on   to   the   computer,   and   the  distance  from  the  wall  to  where  the  laser  was  projected  from  will  be  calculated.  The  webcam  and  laser  set-­‐up  will  then  be  moved  around  to  vary  the  distance.  See  Figure  1  for  a  picture  of  the  webcam  and  laser  set-­‐up  as  well  as  the  theory  behind  the  measurements.    Specifically,   the   live   video   stream   from   the   webcam   will   be  displayed   on   the   computer   screen.   Since   the   display   area   will   be  known,  it  will  be  possible  to  see  how  many  pixels  away  the  laser  dot  is   from   the   center   of   the   screen   (pfc).   Thus,   also   knowing   the  distance  between   the  center  of   the  camera   lens  and   the  center  of  the   laser   lens,  triangula?on  can  be  used  to  determine  the  distance  to  the  wall.  The  experimental  results  will  be  compared  to  the  actual  distances  to  determine  the  accuracy  of  the  laser  system.  

Methods  and  Materials  

The   black   background   used   during   the   experiment   was   necessary  because   of   the   difficulty   recognizing   the   laser   through   the   Matlab  soAware.  There  were  not  enough  parameters  to  filter  out  the  excess  noise;   the  main  parameter  used   to   siA   through   the  noise  was   a   red  threshold  that  would  only  take  pixel  values  above  a  certain  value.  As  a  result,  other  red  objects  that  were  not  intended  to  get  detected  were  uninten?onally   detected.   The   implica?on   of   this   is   that   in   real-­‐life  situa?ons,  the  background  of  the  laser  projec?on  will  not  always  be  a  perfectly  uniform  colour,  thus  further  measures  must  be  taken.    To  improve  the  reliability  of  the  laser  set-­‐up,  further  parameters  could  have  been   implemented.  For   instance,   the  detec?on  size  could  have  been  reduced  to  sizes  near  the  laser  dot  size,  which  would  filter  out  a  lot  of  unintended   red  objects.  As  well,   since   the   laser   is  fixed   to   the  camera,  the  laser  dot  projec?on  on  the  computer  screen  will  only  shiA  in   a   linear   fashion   in   one   axis.   This   means   that   the   detec?on   area  could   be   reduced   to   only   a   rectangular   sliver   along   the   axis   of  movement.   Finally,   infrared   lasers   should   be   used   in   order   to  completely   filter   out   most   of   the   visible   spectrum,   which   would  simplify  the  detec?on  of  the  laser  dot.  

Discussion  

Through  this  research  project  it  was  determined  that  implemen?ng  a  laser-­‐distancing  system  is  feasible.  The  average  percent  error  of  5.46%  indicated   that   the   triangula?on   method   used   for   calcula?ng   the  distance  between  the  laser  and  the  wall  was  accurate.      Future   improvements   to   laser-­‐distancing   systems   would   include  implemen?ng  more  parameters  to  filter  out  the  laser  dot.  A  possible  parameter  would  be  to  reduce  the  detec?on  size   to  near   the  size  of  the   laser  dot.  As  well,  an   infrared   laser  could  be  used   to  completely  filter  out  the  visible  spectrum,  thus  simplifying  the  detec?on  process.    The  next  step  would  be  to  apply  this  model  from  Matlab  to  create  an  actual   implementa?on   on   the   small   helicopter   UAV   from   Tyto  Robo?cs  (see  Figure  4).  This  would  require  hardcode  to  be  wriken  for  the  specific  microchip  of  the  UAV.  The  en?re  laser-­‐distancing  system  for   the   UAV   would   have   to   meet   the   requirements   of   being   both  lightweight  and  energy-­‐efficient,  in  addi?on  to  being  able  to  share  the  same  camera  as  the  one  used  for  detec?ng  the  op?cal  flow.  

Conclusions  

PFC  (pix)   Experimental  D  (cm)   Actual  D  (cm)   %  Error  

109   32.99   30   9.97  

84   52.62   50   5.23  

70   78.87   75   5.16  

63   105.08   100   5.08  

59   129.70   125   3.76  

56   157.36   150   4.90  

54   183.43   175   4.82  

52   219.85   200   9.93  

Results  

Figure  1.  Sonar,  camera,  and  laser  set-­‐up  (leA)1;  Sonar  distancing  (top  right)4;  laser  distancing  using  a  camera  (bokom  right)5.  

Table  1.  Experimental  distances  compared  to  actual  distances  measured  at  different  pixels  from  center  (PFC).  

Figure  3.  Graphical  representa?on  of  experimental  vs.  actual  distance.  

0  

50  

100  

150  

200  

250  

109   84   70   63   59   56   54   52  

Distan

ce  (cm)  

Pixels  From  Centre  (pix)  

Experimental  D  (cm)  Actual  D  (cm)  

Figure  2.  Laser  dot  through  a  camera-­‐lens  at  close  range  (leA)  and  at  far-­‐range  (right)2.        

Figure  4.  The  UAV  being  developed  by  Tyto  Robo?cs  that  would  benefit  from  implemen?ng  a  laser-­‐distancing  system  (no?ce  the  small  size)3.  

Acknowledgements  University  of  Okawa  Faculty  of  Engineering  Undergraduate  Research  Opportunity  Program  

Sonar