ロボティクスとオートメーションの進歩

Ureteropelvic junction obstruction is a common clinical entity in urological practice. The obstruction can result from intrinsic or extrinsic factors. The clinical course is variable due to degree of obstruction. Diagnose is usually made by contrast-enhanced excretory imaging modalities and nuclear scan. Open surgical, laparoscopic and robotic assisted laparoscopic approaches are the available surgical treatment options. In this case report, we present a congenital ureteropelvic junction obstruction treated with robotic assisted transperitoneal pyeloplasty with many intracalyceal stones surprisingly noticed during surgery and successfully treated in the same session.

This work aims to describe another contemporary manner for interaction between human and mechatronic
device by Bluetooth communication with a purpose for implementing wireless remote motion control of an educational mobile robot.

The Artificial Immune System (AIS) is a biologically inspired computation system based on specifically human immune system. AIS applications in last one decade have been developed to address the complex computational and engineering problems related to classification, optimisation and anomaly detection. Many investigations have been conducted to understand the principles of immune system to translate the knowledge into AIS applications. However, a clear understanding of principles and responses of immune system is still required for application of AIS to Swarm Robotics. This article after a review of AIS models and algorithms proposes an integration of AIS and Swarm Robotics by developing a very clear understanding of immune system structures and associated functions.

Unmanned aircraft systems (UAS) are playing increasingly prominent roles in defense programs and defense strategies around the world. Technology advancements have enabled the development of it to do many excellent jobs as reconnaissance, surveillance, battle fighters, and communications relays. Simulating a small unmanned aerial vehicle (SUAV) dynamics and analyzing its behavior at the preflight stage is too important and more efficient. The first step in the UAV design is the mathematical modeling of the nonlinear equations of motion. A survey with a standard method to obtain the full non-linear equations of motion is utilized, and then the linearization of the equations according to a steady state flight condition (trimming) is derived. This modeling technique is applied to an Ultrastick-25e fixed wing UAV to obtain the valued linear longitudinal and lateral models. At the end, the behavior of the states of the non-linear UAV and the resulted linear model is compared by applying a doublet signals in the control surfaces to check the matching between them.