This paper presents a novel approach for obstacle representation method when robotic manipulation task system
understand real indoor environment for 3D workspace modeling. When many objects scattering on the table in
workspace, if the robot want to grasp only one object, the robot system should has a path planning to approach the object.
In this case, the obstacle representation in cluttered-environment is an important role for robot system. The research area
of 3D workspace modeling, the research of step by step accumulating environment observation method is more difficult
than the entire environment observing method and the research is not reported sufficiently. In this paper, we can
contribute the two issues for real-time 3D workspace modeling to using the sequential input stereopsis scenes
information. First, we can suggest a method to estimate the transformation matrix from using SIFT feature and Epipolar
Geometry Constraint characteristics in the continuous process of accumulating sequential input stereopsis scenes for
more fast and accurate than recently research. This method guarantees a feasible transformation matrix result better than
the using traditional ICP and general SIFT method. Second, we can suggest a method for octree-based obstacle
representation and we can also suggest an octree update method for real-time. It is faster than entire workspace
observation method, and if the robot doesn't know about the objects and obstacles information in workspace, we can
help the robot to understand environment himself from practical information. Taking the obstacle information from
above method can help the robot system possible to do path planning for robotic manipulation task in 3D workspace.
Through the experimental result, we can show that our method is well-performing and well-modeling the obstacle in 3D
real environment workspace modeling in real-time.
In this paper we propose a method of optimal camera exposure estimation in the image for a structured light system. In
structured light system, it is important to discriminate the patterns form the captured images which are illuminated by the
projector. But every object in real environments has a different reflection due to object's material and surface's color
property, so the precise discrimination of the projected pattern from the image in indoor environments is a hard problem
where many objects are located together especially. And the camera exposure setting is not good. For better 3D range
data, we estimate the optimal exposure at pixels so that makes the illuminated light by the projector can be captured
properly by the camera. In order to obtain the optimal exposures about specific environments in structured light system,
we should know how much intensity and/or brightness varies while the exposure is changed. So we introduce the novel
method to estimate intensity by characteristic curves. This proposed method overcomes the conventional method's
exposure problem and presents what is the optimal exposure at pixels is and how to obtain this setting. This has been
proved to be feasible in many applications which need to measure the objects with different surface properties.