TY - GEN
T1 - MCL-based global localization of cleaning robot using fast rotation-invariant corner matching method
AU - Kwon, Tae Bum
AU - Song, Jae Bok
AU - Kang, Sung Chul
PY - 2010
Y1 - 2010
N2 - Mobile robot navigation with ceiling features such as a corner which is one of the most popular visual features used in robotics has been widely studied because of its practicality and high performance, and recently low-cost robots have started to use this navigation technique. A cleaning robot is a good example. This study is focused on global localization of a cleaning robot and MCL, one of the popular localization methods, was used with ceiling corners. However, MCL-based global localization is a very time consuming task even on a PC, and so a fast rotation-invariant corner matching method was proposed in this study to reduce the time of global localization with corner features. A pixel-based sum of squared differences (SSD) method has been widely used for corner matching. However, because this method cannot match corners with rotation changes, it is unsuitable for a cleaning robot where corners observed from the robot have rotation changes. In our approach, the image around a corner is divided into some partitions and the representative values of all partitions are computed to generate a rotation-invariant descriptor. This descriptor consists of a small number of values, and two descriptors are simply compared to match two corners. Various experiments on a PC and an embedded system verify that matching by the proposed method is very fast and invariant to a rotation change, and is more suitable for a cleaning robot than the pixel-based SSD method. Moreover, global localization can be conducted using this matching method.
AB - Mobile robot navigation with ceiling features such as a corner which is one of the most popular visual features used in robotics has been widely studied because of its practicality and high performance, and recently low-cost robots have started to use this navigation technique. A cleaning robot is a good example. This study is focused on global localization of a cleaning robot and MCL, one of the popular localization methods, was used with ceiling corners. However, MCL-based global localization is a very time consuming task even on a PC, and so a fast rotation-invariant corner matching method was proposed in this study to reduce the time of global localization with corner features. A pixel-based sum of squared differences (SSD) method has been widely used for corner matching. However, because this method cannot match corners with rotation changes, it is unsuitable for a cleaning robot where corners observed from the robot have rotation changes. In our approach, the image around a corner is divided into some partitions and the representative values of all partitions are computed to generate a rotation-invariant descriptor. This descriptor consists of a small number of values, and two descriptors are simply compared to match two corners. Various experiments on a PC and an embedded system verify that matching by the proposed method is very fast and invariant to a rotation change, and is more suitable for a cleaning robot than the pixel-based SSD method. Moreover, global localization can be conducted using this matching method.
KW - Ceiling corner
KW - Cleaning robot localization
KW - Rotation-invariant corner matching
UR - http://www.scopus.com/inward/record.url?scp=78751550197&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:78751550197
SN - 9781424474530
T3 - ICCAS 2010 - International Conference on Control, Automation and Systems
SP - 1988
EP - 1992
BT - ICCAS 2010 - International Conference on Control, Automation and Systems
T2 - International Conference on Control, Automation and Systems, ICCAS 2010
Y2 - 27 October 2010 through 30 October 2010
ER -