RESUMO
Appendiceal diverticulitis is an uncommon condition that clinically resembles acute appendicitis. However, it is an incidental finding in histopathological studies and is rarely diagnosed preoperatively by imaging studies. In this article, we present the clinical and imaging findings of a male patient presenting with right upper quadrant pain with a preoperative imaging diagnosis of appendiceal diverticulitis. He underwent laparoscopic appendectomy and confirmed the diagnosis of appendiceal diverticulitis. This is a rare preoperative diagnosis. The management is often like typical appendicitis which is appendectomy. It is important to differentiate it from diverticulitis of the small intestine or colon because these diseases usually require only conservative treatment.
RESUMO
This paper introduces a Hexa parallel robot and obstacle collision detection method based on dynamic modeling and a computer vision system. The processes to deal with the collision issues refer to collision detection, collision isolation, and collision identification applied to the Hexa robot, respectively, in this paper. Initially, the configuration, kinematic and dynamic characteristics during movement trajectories of the Hexa parallel robot are analyzed to perform the knowledge extraction for the method. Next, a virtual force sensor is presented to estimate the collision detection signal created as a combination of the solution to the inverse dynamics and a low-pass filter. Then, a vision system consisting of dual-depth cameras is designed for obstacle isolation and determining the contact point location at the end-effector, an arm, and a rod of the Hexa robot. Finally, a recursive Newton-Euler algorithm is applied to compute contact forces caused by collision cases with the real-Hexa robot. Based on the experimental results, the force identification is compared to sensor forces for the performance evaluation of the proposed collision detection method.
