The object of interest is not required to appear in a specific location, orientation, or depth, nor is it required to remain motionless during the grasp. The proposed system was derived using the Controlled Active Vision framework and provided the flexibility to robustly interact with the environment in the presence of uncertainty. The proposed approach was experimentally verified using the MRVT system to automatically select targets of interest and to guide the manipulator in the grasping of a target. More recently, the grasping system was expanded and improved with the use of pressure snakes . We have also worked on a model-based approach for visual tracking and servoing in robotics.
Deformable models imitate, in real-time, the dynamic behavior of elastic structures.
They consist of several hundred control points that are processed in parallel. Experimental results show that the deformable models achieve robust tracking even when the target is partially occluded. These techniques have been applied to assembly tasks that involve a combination of computer vision and force robot control. All rights reserved. The University of Minnesota is an equal opportunity educator and employer.