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. © 2013 IEEE

In this paper, we present a system capable of automatically steering a bevel-tipped flexible needle under ultrasound guidance toward a physical target while avoiding a physical obstacle embedded in gelatin phantoms and biological tissue with curved surfaces. An ultrasound pre-operative scan is performed for three-dimensional (3D) target localization and shape reconstruction. A controller based on implicit force control is developed to align the transducer with curved surfaces to assure the maximum contact area, and thus obtain an image of sufficient quality. We experimentally investigate the effect of needle insertion system parameters such as insertion speed, needle diameter and bevel angle on target motion to adjust the parameters that minimize the target motion during insertion. A fast sampling-based path planner is used to compute and periodically update a feasible path to the target that avoids obstacles. We present experimental results for target reconstruction and needle insertion procedures in gelatin-based phantoms and biological tissue. Mean targeting errors of 1.46 ± 0.37 mm, 1.29 ± 0.29 mm and 1.82 ± 0.58 mm are obtained for phantoms with inclined, curved and combined (inclined and curved) surfaces, respectively, for insertion distance of 86–103 mm. The achieved targeting errors suggest that our approach is sufficient for targeting lesions of 3 mm radius that can be detected using clinical ultrasound imaging systems.

Abstract-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 FBGsensor 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 FBGsensor 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.