November/December 2021 69THE ROBOT CORRAL
First, we set up three 8 x 8–foot pens, each with a different f loor sur-
face, where we could repeat cleaning scenarios for each model. The
f loor of one corral was low- to medium-pile carpet; the second was
bare, polished concrete; and the third was laminate f looring. We
placed a floormat and a wooden stool on the concrete as obstacles.
Then, in each corral, we dumped five grams of f lour, five grams
of sawdust, 15 grams of dried rice, and 15 grams of pinto beans
to simulate various types of dirt and debris. (We should note that
robot vacuums are maintenance cleaners, and these—for the sake
of our stress test—were more material than you should expect a
vac to pick up on a regular basis.) On the carpet, f lour and sawdust
are indicators of how well a vacuum’s brushes work at agitating
dirt, making it easier to suck up. On the laminate, where sawdust
and f lour can get deep into seams, raw suction power is needed.
And dried rice and pinto beans are a challenge on concrete and
laminate, because a vacuum’s brushes could quickly scatter them.
Once we had the vacuums’ apps installed and paired, we set the
models loose, timing and scrutinizing their work.
Navigation is key to how well a robot vacuum performs
its job. It doesn’t matter how much suction one has if it
doesn’t pass over every inch of the f loor. Just about all
models employ three basic types of sensors to help them
navigate. (See the sidebar at right for a primer on the
most prevalent types of systems.) As the ones we tested worked their way through
our corrals and one editor’s living room that we used as a control, we took stock of
how efficiently they moved within the space. Below are our findings on the three best.
Bump-and-Go / The vacuum
heads in one direction, and then
changes course when it hits
something. Many vacuums have
programming that makes their
paths more efficient. By bumping
into a wall in a couple of places,
they can verify the location of
a wall and travel parallel to it,
turning 180 degrees each time
they hit an end wall.vSLAM / Visual Simultaneous
Localization and Mapping (vSLAM)
tracks multiple points in a room,
in successive camera frames, to
triangulate position. The Roomba
S9+ employs this method to
navigate. Over time it learns and
becomes more efficient, where
it may rely on points that remain
constant and do not change.LiDAR / Light Detection and
Ranging uses a laser to locate
features by sending out pulses of
light and measuring how long they
take to return. LiDAR is especially
useful for creating accurate
maps and is the most powerful
navigation tool for robot vacuums.CRITIQUING
THEIR
NAVIGATION
IROBOT ROOMBA S9+
We had the most difficulty
discerning what the S9+ was
actually doing. What initially
appeared to be a sort of
random path, we realized,
was a series of location
exercises using vSLAM. It
first moved left and right,
bumping both sides in
multiple places, and then it
worked toward the corners,
looping into them in a wide
curve before moving tight in
and backing out. Then it
performed a trip around the
perimeter, and then into the
corners again. After all that, it
moved to make left/right
passes to cover the middle
area. Finally, it vacuumed left
and right of the dock.ROBOROCK S6 MAXV
Using both vSLAM and
LiDAR to navigate, the S6
MaxV started with an odd,
diagonal zigzag that we
hadn’t seen robot vacuums
use before, presumably
scanning the surroundings.
Presumably, we say,
because it then quickly
went around the perimeter
of the corral, following that
up with a series of out-and-
back passes moving across
the whole space. The
vacuum then performed a
second pass of the
perimeter, ending with a
final out-and-back series of
sweeps across the corral
before returning to the
dock to top off the battery.
EUFY G30 EDGE
Despite having a lower-tech
bump-and-go navigation
system, the Eufy seemed
remarkably methodical
and efficient. Leaving the
dock, it immediately started
a straight out-and-back
pattern, moving left to the
wall with each pass. It then
bumped the wall in a couple
of places, confirming its
location, before returning to
the center. It continued out
and back to the right wall,
where it started around the
perimeter to the lower left
corner. It then began left/
right passes from the front
to the back, followed by the
perimeter, ending with the
lower right corner.THERE ARE THREE COMMON
NAVIGATION SYSTEMS: