Graphics Reference
In-Depth Information
Chapter 2
Consumer Robotics: A Platform
for Embedding Computer Vision
in Everyday Life
Mario E. Munich, Phil Fong, Jason Meltzer and Ethan Eade
Abstract Consumer robotic devices provide a platform for embedded computer
vision algorithms in applications for everyday life. The consumer market is very
price-sensitive, so robots must be developed with a single task in mind, aiming
to provide the best performance at the lowest cost. Computational resources in
consumer robotics are scarce given cost constraints, forcing the design of novel
algorithms that elegantly incorporate such constraints. We present a graph-based
SLAMapproach designed to operate on computationally constrained platforms using
monocular vision and odometry. When computation and memory are limited, visual
tracking becomes difficult or impossible, and costs for map representation and updat-
ing must remain low. Our system constructs a map of structured views using only
weak temporal assumptions and performs recognition and relative pose estimation
over the set of views. We fuse visual observations and differential measurements
in an incrementally optimized graph representation. Using variable elimination and
constraint pruning, graph complexity and storage is kept linear in explored space
rather than growing over time. We evaluate performance on sequences with ground
truth and also compare to a standard graph-SLAM approach.
2.1 Introduction
Over the past decade, computer vision algorithms have transitioned from the lab to
the marketplace. Improvements in processors, memory density, and image sensor
technology enable the deployment of sophisticated algorithms. The introduction
( B ) · P. Fong · J. Meltzer
iRobot, Pasadena, CA, USA
e-mail: mmunich@irobot.com
P. Fong
e-mail: pfong@irobot.com
J. Meltzer
e-mail: jmeltzer@irobot.com
E. Eade
Microsoft Research, Redmond, WA, USA
e-mail: ethan@ethaneade.com
M.E. Munich
 
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