著者
上田 隆一 新井 民夫 浅沼 和範 梅田 和昇 大隅 久
出版者
The Robotics Society of Japan
雑誌
日本ロボット学会誌 (ISSN:02891824)
巻号頁・発行日
vol.23, no.4, pp.466-473, 2005-05-15 (Released:2010-08-25)
参考文献数
18
被引用文献数
4 8

Though Monte Carlo localization is a popular method for mobile robot localization, it requires a method for recovery of large estimation error in itself. In this paper, a recovery method, which is named an expansion resetting method, is newly proposed. The combination of the expansion resetting method and the sensor resetting method, which is a typical resetting method, is also proposed. We then compared our methods and others in a simulated RoboCup environment. Typical accidents for mobile robots were produced in the simulator during trials. We could verify that the expansion resetting method was effective for recovery from small irregular changes of a robot's pose, and that the combination method could deal with both large and small irregular changes.
著者
柴田 雅聡 生形 徹 寺林 賢司 モロ アレサンドロ 梅田 和昇
出版者
一般社団法人 日本ロボット学会
雑誌
日本ロボット学会誌 (ISSN:02891824)
巻号頁・発行日
vol.32, no.6, pp.558-565, 2014 (Released:2014-08-15)
参考文献数
24

In this paper, a human detection method that combines information of segmented range image and human detectors based on image local feature is proposed. The method uses a stereo vision system called Subtraction Stereo, which extracts foreground information and range image. Range image is segmented for every object by Mean Shift Clustering. The proposed method reduces processing time and false detection by limiting the search range to the object. Joint HOG feature is used for human detection and reduces undetected human by integration of detection windows in consideration of occulusion. The proposed method is evaluated by experiments comparing with the method using the conventional Joint HOG feature.