Cardiovascular disease is one of the leading causes of death in the United States and also a major disease nationwide. Over 700,000 coronary artery bypass graft (CABG) procedures are performed annually all around the ...
Cardiovascular disease is one of the leading causes of death in the United States and also a major disease nationwide. Over 700,000 coronary artery bypass graft (CABG) procedures are performed annually all around the world, of which 350,000 are performed in the United States. The use of mechanical stabilizers to isolate and immobilize the surface region of the heart is not without its limitations such as hemodynamic deterioration, and arrythmia induction requiring inotropic support. Consequently, the use of mechanical stabilizers leads to a poor immobilization of the surgical field in spite of significant forces of traction and retraction used with these devices. The primary goal of this research is to develop effective haptic (sense of touch) and visual servoing methods with the long-term goal of eliminating the need for mechanical stabilizers and extracorporeal support for CABG procedures. We present in this paper the results from our initial work in the area of tracking a deformable membrane using vision and providing haptic feedback to the user, based on the visual information through the vision hardware and the material properties of the membrane. In our first experiment, we track the deformation of a rubber membrane in real-time through stereovision while providing haptic feedback to the user interacting with the reconstructed membrane through the PHANToM haptic device. In the second experiment, we verify the ability of our vision system to track a point on a surface undergoing a complex 3D motion.
作者：
J.P. DesaiProgram of Robotics
Intelligent Sensing and Mechatronics PRISM Laboratory MEM Department Drexel University Philadelphia PA USA
Addresses the control of a team of robots navigating in a terrain with obstacles, while maintaining a desired formation and changing formations when required using an underlying graph theoretic framework. We state and...
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Addresses the control of a team of robots navigating in a terrain with obstacles, while maintaining a desired formation and changing formations when required using an underlying graph theoretic framework. We state and prove the mathematical results relating to multi-robot teams moving in a formation. We model each team as a triple, (g, r, /spl Hscr/), consisting of a group element, g, that describes the gross position of the lead robot, a set of shape variables, r, that describes the relative positions of robots and a control graph, /spl Hscr/ that describes the behaviors of the robots in the formation. Our framework enables the representation and enumeration of all possible control graphs, and the coordination of transitions between any two control graphs. Further, we describe an algorithm that allows the team of robots to move between any two formations, while avoiding obstacles. As the number of robots increases, the number of possible control graphs increases. However, because the control computations are decentralized, the algorithms scale with the number of robots. We present an example to illustrate the control graphs and the algorithm for transitioning. between them in the presence and absence of sensor noise.
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