Needle insertion procedures are commonly performed in current clinical practice for diagnostic and therapeutic purposes. Although prevailing technology allows accurate localization of lesions, they cannot yet be precisely targeted. Needle steering is a promising technique to overcome this challenge. In this paper, we describe the development of a novel steering system for an actuated-tip flexible needle. Strain measurements from an array of Fiber Bragg Grating (FBG) sensors are used for online reconstruction of the needle shape in 3D-space. FBG-sensor data is then fused with ultrasound images obtained from a clinically-approved Automated Breast Volume Scanner (ABVS) using an unscented Kalman filter. A new ultrasound-based tracking algorithm is developed for the robust tracking of the needle in biological tissue. Two experimental cases are presented to evaluate the proposed steering system. In the first case, the needle shape is reconstructed using the tracked tip position in ultrasound images and FBG-sensor measurements, separately. The reconstructed shape is then compared with the actual 3D needle shape obtained from the ABVS. In the second case, two steering experiments are performed to evaluate the overall system by fusing the FBG-sensor data and ultrasound images. Average targeting errors are 1.29±0.41 mm and 1.42±0.72 mm in gelatin phantom and biological tissue, respectively.

Minimally invasive surgery assisted by robots is characterized by the restriction of feasible motions of the manipulator link constrained to move through the entry port to the patient's body. In particular, the link is only allowed to translate along its axis and rotate about the entry point. This requires constraining the manipulator motion with respect to a point known as Remote Center of Motion (RCM). The achievement of any surgical task inside the patient's body must take into account this constraint. In this paper we provide a new, general characterization of the RCM constraint useful for task control in the minimally invasive robotic surgery context. To show the effectiveness of our formalization, we consider first a visual task for a manipulator with 6 degrees of freedom holding an endoscopic camera and derive the kinematic control law allowing to achieve the visual task while satisfying the RCM constraint. An example of application of the proposed kinematic modeling to a motion planning problem for a 9 degrees of freedom manipulator with assigned path for the surgical tool is then proposed to illustrate the generality of the approach.

We present a new image-based visual servoing scheme for tracking moving targets. This is achieved with a twofold approach. First, we devise a straightforward adaptation of a previously proposed depth observer to account for the fact that the target is not stationary. Second, we estimate the disturbance on the visual feature dynamics due to the target motion, and we add a related compensation term to the visual controller. In particular, the target velocity components parallel to the image plane are reconstructed using a disturbance observer, whereas the orthogonal component is retrieved from the measurement of the Focus Of Expansion. Comparative experiments show that the proposed method can improve over classical visual servoing schemes by 50% or more.

This paper traces the evolution of the distributed test strategy at Intel, covering both the tester platform, which is now on the 2nd generation, as well as the parallel evolution of the test content, which is optimized for this platform. We describe the distribution of Pentium/spl reg/ 4 processor test content between structural and functional platforms, associated fallout, and key issues encountered with content migration. Finally, we discuss future test content and platform trends as shaped by increasing device complexity and defect types.