IEEE Robotics & Automation Magazine - December 2013 - 83

© ISTO
CKPH
OTO.C
OM/JIR
SAK

Embedded
Visual SLAM

By Seongsoo Lee and Sukhan Lee

Applications for Low-Cost Consumer Robots

A

camera poses a highly attractive choice as a sensor in
implementing simultaneous localization and mapping (SLAM) for low-cost consumer robots such
as home cleaning robots. This is due to its low
cost, light weight, and low power consumption.
However, most of the visual SLAMs available to date are not
designed and, consequently, not suitable for use in a low-cost
embedded SLAM for consumer robots. This article presents
a computationally light yet performance-wise robust SLAM
algorithm and its implementation as an embedded system
for low-cost consumer robots using an upward-looking camera. Especially for a large-scale mapping of indoor environments, methods of pose graph optimization as well as submapping are employed. An occupancy grid map is used to
integrate an efficient Kalman filter-based localization into a
SLAM framework. Furthermore, an algorithmic visual compass is introduced as a means of reducing the computational
complexity involved in pose graph optimization, taking
advantage of the distinct geometric features of the scenes
captured by an upward-looking camera. The proposed
visual SLAM is implemented in a real home cleaning robot
Digital Object Identifier 10.1109/MRA.2013.2283642
Date of publication: 31 October 2013

1070-9932/13/$31.00©2013IEEE

as an embedded system using an ARM11 processor.
Extensive test results demonstrate the power of the proposed
embedded visual SLAM in terms of not only its computational efficiency but also its performance robustness in realworld applications.
Visual SLAM-A Key Technology
for Low-Cost Mobile Robots
SLAM represents a key technology for a mobile robot to selfnavigate in an unknown environment. It automatically constructs a map of its environment while simultaneously determining its pose on the map being constructed [7].
Visual SLAM has been the focus of many recent studies
due to the remarkable advancement in the performance of
low-cost vision systems, which provide abundant information
on the environment. A simple camera, with its small size, light
weight, and low energy requirement, is useful as an integrated
sensor that can be easily embedded in most mobile robots,
especially for consumer robots.
Monocular Camera-Based Approach
Several approaches to visual SLAM that employ a monocular
camera have been proposed [4], [5], [18]. In [4], a monocular
camera SLAM algorithm without odometry is proposed for
DECEMBER 2013

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