Hand Motion Detection for Observation-Based Assistance in a Cooperation by Multiple Robots
In a cooperation task by multiple 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 proposes a method for such an indirect cooperation based on an observation by the partner robot. The observing robot obtains corresponding points of Scale-Invariant Feature Transformation (SIFT) on the working robot with hand and the target object from multiple captured images. The 3-D position of the target object and hand motion of the working robot can be detected by applying stereo vision theory to the points. The working robot is then able to get the relation between its hand and the target object indirectly from the observing robot. We describe each process to establish the indirect cooperation. Fundamental experiments confirmed the validity of presented method.
KeywordsRobot vision Cooperation by observation Scale-Invariant Feature Transformation (SIFT) Stereo vision
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