Active filtering of physiological motion in robotized surgery using predictive control

Abstract

Abstract-This paper presents a predictive control approach to active mechanical filtering of complex, periodic motions of organs induced by respiration or heart beating in robotized surgery. Two different predictive control schemes are proposed for the compensation of respiratory motions or cardiac motions.For respiratory motions, the periodic property of the disturbance has been included into the input-output model of the controlled system so as to have the robotic system learn and anticipate perturbation motions. A new cost function is proposed for the unconstrained generalized predictive controller (GPC) where reference tracking is decoupled from the rejection of predictable periodic motions.Cardiac motions are more complex since they are the combination of two periodic non-harmonic components. An adaptive disturbance predictor is proposed which outputs future predicted disturbance values. These predicted values are used to anticipate the disturbance by using the predictive feature of a regular GPC.Experimental results are presented on a laboratory testbed and in vivo on pigs. They demonstrate the effectiveness of the two proposed methods to compensate complex physiological motion.

Optical techniques for 3D surface reconstruction in computer-assisted laparoscopic surgery

“…Despite acceptable performance, lag remains an issue, and this is compounded by other computational tasks such as registration or biomechanical modelling, which are currently not real-time in general. In the case of robotic control loops, where measurements are used for example to synchronize with the physiological motion of tissues, much higher run times are required to avoid aliasing the motion signals (Ginhoux et al, 2005). Currently, these cannot be achieved for dense parts of the operating field of view in HD video due to the data throughput and computational demands, but predictive models could potentially be a solution.…”

“…This is typically achieved with iterative strategies such as optical flow (Horn and Schunck, 1981;Lucas and Kanade, 1981), which are based on the knowledge of the location of a feature in the previous frame to constrain a search for the corresponding feature in the next frame, assuming a small degree of motion and intensity coherence. Iterative strategies have been combined with predictive models of feature localization based on prior knowledge of anatomical periodicity, machine learning approaches and predictive filtering (Ginhoux et al, 2005;Ortmaier et al, 2005;Bachta et al, 2009;Bogatyrenko et al, 2011;Richa et al, 2010;Giannarou et al, 2012;Mahadevan and Vasconcelos, 2009;Puerto Souza et al) and have been extensively used in laparoscopic images with varying degrees of success (Sauvee et al, 2007;Elhawary and Popovic, 2011;Ortmaier et al, 2005;Yip et al, 2012).…”

Development of a Robotic System to Enable Beating-heart Surgery

“…This can be done by continually taking images of the heart and surgical tool with a camera or medical scanner. High-speed cameras can be used to visualize the exterior surface of the heart [4] and ultrasound images can be used to visualize both the exterior and the interior surfaces of the heart [5]. In addition, sonomicrometry crystals can be sutured to the heart to track the position of a specific point on the heart [6]; as it is not practical to suture sonomicrometry crystals to the heart during surgery, this method is more appropriate for validation of control techniques.…”

“…Choosing the type of controller depends on whether the first element's measurement of the surgical tool and beating heart positions introduces a delay. When a high-speed camera captures the positions, a generalized predictive controller can be used [4]. If a delay is introduced by the first element, however, the current position of the heart must be estimated.…”

Visual Servoing via Nonlinear Predictive Control

“…Advanced control laws such as optimal control [14,22], adaptive control [21], LMIs [9,10] and predictive control [2,3,12,13,23] have been reported in the literature. In [12,13], a predictive controller is used for motion compensation in target tracking applications. The prediction of the target motion is used to reject perturbation in order to cancel tracking errors.…”