Title
Generalized measuring-worm algorithm: high-accuracy mapping and movement via cooperating swarm robots
Abstract
Recently, many extensive studies have been conducted on robot control via self-positioning estimation techniques. In the simultaneous localization and mapping (SLAM) method, which is one approach to self-positioning estimation, robots generally use both autonomous position information from internal sensors and observed information on external landmarks. SLAM can yield higher accuracy positioning estimations depending on the number of landmarks; however, this technique involves a degree of uncertainty and has a high computational cost, because it utilizes image processing to detect and recognize landmarks. To overcome this problem, we propose a state-of-the-art method called a generalized measuring-worm (GMW) algorithm for map creation and position estimation, which uses multiple cooperating robots that serve as moving landmarks for each other. This approach allows problems of uncertainty and computational cost to be overcome, because a robot must find only a simple two-dimensional marker rather than feature-point landmarks. In the GMW method, the robots are given a two-dimensional marker of known shape and size and use a front-positioned camera to determine the marker distance and direction. The robots use this information to estimate each otheru0027s positions and to calibrate their movement. To evaluate the proposed method experimentally, we fabricated two real robots and observed their behavior in an indoor environment. The experimental results revealed that the distance measurement and control error could be reduced to less than 3 %.
Year
DOI
Venue
2016
10.1007/s10015-016-0301-x
Artificial Life and Robotics
Keywords
DocType
Volume
Swarm robotics, Movable landmarks, Camera positioning system, Self-localization estimation, Robot corroboration, Planetary exploration autonomous rover
Journal
21
Issue
ISSN
Citations 
4
1614-7456
0
PageRank 
References 
Authors
0.34
1
9
Name
Order
Citations
PageRank
Kiyohiko Hattori1139.22
Eri Homma200.34
Toshinori Kagawa383.34
Masayuki Otani482.77
Naoki Tatebe501.35
Yasunori Owada6105.35
Lin Shan723.77
Katsuhiro Temma8267.35
Kiyoshi Hamaguchi98216.05