Authors:
Toyomi Fujita
and
Kento Yamada
Affiliation:
Tohoku Institute of Technology, Japan
Keyword(s):
Robot Vision, Cooperation by Observation, SIFT (Scale-Invariant Feature Transformation), SURF (Speeded Up Robust Features), Stereo Vision.
Related
Ontology
Subjects/Areas/Topics:
Image Processing
;
Informatics in Control, Automation and Robotics
;
Mobile Robots and Autonomous Systems
;
Robotics and Automation
;
Vision, Recognition and Reconstruction
Abstract:
In some practical work by robots, it may happen that a working robot can not detect a target object for handling
due to a sensor occlusion. In this situation, if another cooperative robot observes the working robot with the
target object and detects their positions and orientations, it will be possible for the working robot to complete
the handling task. Such behavior is a kind of indirect cooperation. This study considers a method for such
an indirect cooperation based on an observation by the partner robot. The observing robot will be able to
perform such a cooperation by obtaining feature points and corresponding points on the working robot with
hand and the target object from multiple captured images, then computing 3-D positions of the targets and
motion of the hand. In this study, we mainly focus on 3-D position detection of the working robot and try
applying SURF (Speeded Up Robust Features) descriptor and a voting method for detecting the feature points
and corresponding poin
ts. The 3-D position of the working robot is then computed from these corresponding
points based on stereo vision theory. Fundamental experiments confirmed the validity of presented method.
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