Cable failure tolerant control and planning in a planar reconfigurable cable driven parallel robot.

The addition of geometric reconfigurability in a cable driven parallel robot (CDPR) introduces kinematic redundancies which can be exploited for manipulating structural and mechanical properties of the robot through redundancy resolution. In the event of a cable failure, a reconfigurable CDPR (rCDPR) can also realign its geometric arrangement to overcome the effects of cable failure and recover the original expected trajectory and complete the trajectory tracking task. In this paper we discuss a fault tolerant control (FTC) framework that relies on an Interactive Multiple Model (IMM) adaptive estimation filter for simultaneous fault detection and diagnosis (FDD) and task recovery.

Dual-Level Knowledge Distillation via Knowledge Alignment and Correlation.

Knowledge distillation (KD) has become a widely used technique for model compression and knowledge transfer. We find that the standard KD method performs the knowledge alignment on an individual sample indirectly via class prototypes and neglects the structural knowledge between different samples, namely, knowledge correlation. Although recent contrastive learning-based distillation methods can be decomposed into knowledge alignment and correlation, their correlation objectives undesirably push apart representations of samples from the same class, leading to inferior distillation results.

Influence of Morbid Obesity on Surgical Outcomes in Robotic-Assisted Gynecologic Surgery.

The aim of this research was to estimate the impact of body mass index (BMI) on surgical outcomes in patients undergoing robotic-assisted gynecologic surgery. This study was a retrospective review of prospectively collected cohort data for a consecutive series of patients undergoing gynecologic robotic surgery in a single institution. BMI, expressed as kg/m, was abstracted from the medical charts of all patients undergoing robotic hysterectomy.

An analysis of the impact of previous laparoscopic hysterectomy experience on the learning curve for robotic hysterectomy.

To analyze and compare the safety and perioperative outcomes of newly trained robotic surgeons with previous laparoscopic hysterectomy experience (TLH Exp) and those without previous laparoscopic hysterectomy experience (Non-TLH Exp). The purpose is to determine the effect of previous advanced laparoscopic skills on the performance in robotic assisted laparoscopic surgery. We will also compare the perioperative outcomes between the total laparoscopic hysterectomies (TLH), and robotic assisted laparoscopic hysterectomies (RALH) of a single experienced (TLH Exp) robotic surgeon.

Evaluation of robotic minimally invasive surgical skills using motion studies.

Robotic Minimally Invasive Surgery, and the engendered computer-integration, offers unique opportunities for quantitative computer-based surgical-performance evaluation. In this work, we examine extension of traditional manipulative skill assessment, having deep roots in performance evaluation in manufacturing industries, for applicability to robotic surgical skill evaluation. This method relies on: defining task-level segmentation of modular sub-tasks/micro-motions called 'Therbligs' that can be combined to perform a given task; and analyzing intra- and inter-user performance variance by studying surgeons' performance over each 'Therbligs'.