Beating heart procedures promise significant health benefits to patients but the fast motion of the heart poses a serious challenge to the surgeon. Robotic motion synchronization to heart movements could facilitate these surgeries, although for intracardiac procedures this requires the development of a predictive filter to compensate for the measurement noise and time delay present in 3D ultrasound imaging. In this paper, we present a quasiperiodic cardiac motion model and apply the extended Kalman filter to estimation of its parameters in real-time. We experimentally demonstrate high accuracy robot tracking to heart motion using this filter.

This paper presents a robotic system capable of using three-dimensional ultrasound to guide a surgical instrument to a tracked target location. Tracking of both the surgical instrument and target was done using image based algorithms on the real-time 3D ultrasound data. The tracking techniques are shown to be especially amenable for execution on powerful graphics processor units. By harnessing a graphics card, it was possible to detect both a surgical instrument and a surgical target at a rate of 25 Hz. The high update rate permits the use of tracked instrument and target locations for controlling a robot. Validation of the system was done in a water tank, where the robot moved the instrument to the target site with a mean error of 1.2 mm

New 3D ultrasound visualization has enabled minimally invasive, beating-heart intracardiac procedures. However, rapid motion of internal heart structures limits the realization of these new procedures. This paper investigates the concept of using a single actuator to compensate for tissue motions which occur largely in one direction. We characterize mitral valve annulus motion and show that it is well approximated by a ID model. The subsequent development of a motion-compensating tool (MCT) is described. The resulting instrument was tested in user trials under a series of positional error and tracking delay conditions. Results indicate that the MCT provides an approximately 50% increase in dexterity and 50% decrease in applied force in comparison to a solid tool. The study also shows that MCT tracking efficacy is highly dependent on tracking delays, indicating the importance of predictive, cyclical control algorithms.

This paper presents a real-time 3D ultrasoundguided robotic system, designed to autonomously navigate a surgical instrument to surgeon-specified target points. The system tracks the instrument in real-time (2 Hz) using image processing. Thus, it does not require tracking of the ultrasound scan head. It makes use of a line detection algorithm and a passive instrument marker, which together report the instrument's position and orientation (6 d.o.f.) from a single ultrasound image. Validation experiments are presented. The system controlled instrument position in a variety of image locations with a mean error of 0.8 mm

Currently, the viability of infrared (IR) as an accurate means of measuring distance depends on extensive prior knowledge of the surface. More specifically, the manner in which a surface scatters, reflects, and absorbs infrared energy is needed to interpret the sensor output as a distance measure. In order to use IR in an unknown environment, one must determine the surface properties during robot operation. The paper details a method of determining the properties of a surface, vis-a-vis infrared reflectance, and subsequently calculating the distance to the surface and the relative orientation of the surface using previously acquired sensory data. We present examples of IR distance measures for various surfaces using known environments as well as examples where the prior knowledge edge has been acquired using sonar sensing. Our results demonstrate that infrared sensors can provide accurate range measurements when used in conjunction with other sensing modalities to fit model parameters during robot operation (i.e. in real-time).