Lagrangian D’Alembert Modeled Maneuverable Autonomous Non-Holonomic Mobile Robot Using a Closed Loop PD Controller

The motivation for this work is to develop a platform for a self-localization device. Such a platform has many applications for the autonomous maneuverable non-holonomic mobile robot classification, which can be used for search and rescue or for inspection devices where the robot has a desired path to follow but because of an unknown terrain, the device requires the ability to make ad-hoc corrections to its movement to reach its desire path. The mobile robot is modeled using Lagrangian d’Alembert’s principle considering all the possible inertias and forces generated, and are controlled by restraining movement based on the holonomic and non-holonomic constraints of the modeled vehicle. The device is controlled by a PD controller based on the vehicle’s holonomic and non-holonomic constraints. An experiment was setup to verify the modeling and control structure’s functionality and the initial results are promising.

UAV Autopilot Design for the AUVSI, UAS International Competition

This paper provides an overview of the first participation of the design developed by the undergraduate students of American University of Sharjah to meet the requirements laid forth in the 2008 Association for Unmanned Vehicle Systems International (AUVSI) Student UAS competition. The overall objective of the competition is to fly autonomously over a GPS waypoint defined route and also to identify and locate ground based targets within a confined area. To meet the objectives an unmanned aircraft is equipped with autonomous functionality and aerial imaging system. A ground station and supportive software to keep track of the aircraft routine and log the raw data gained from the flight is also designed. Achieving complete success depends upon mission elements which include autonomous take-off and landing, autonomous control and waypoint navigation. The onboard equipment used was a flight control computer network, IMU, GPS, an air data system and a camera. Additionally, safety features such as manual override was also installed. Presented in this report are aircraft design and testing, the processes involved in accomplishing the goal, and the results and achievements.

Mechanical Test of FPCB and Failure Analysis by Simulation

The paper mainly presented mechanical test and failure analysis methods to reliability study of a new FPCB (Flexible Printed Circuit Boards). Mechanical tests include flexural test, tensile test and flexural fatigue and ductility test. As to simulation analysis, the stress distributions of FPCB under bending and tensile conditions were gained by simulations. Through in-depth analysis of the testing results, the mechanical reliability of FPCB was known detailed. The research provides an approach to improve FPCB performance.

Computations of SIFs for Non-Symmetric V-Notched Plates by the FFEM

The present paper further develops The Fractal-like Finite Element Method (FFEM) to compute the stress intensity factors (SIFs) for non-symmetrical configurations of sharp V-notched plates. The use of global interpolation functions (GIFs) in the FFEM significantly reduces the number of unknown variables (nodal displacements) in a singular region surrounding a singular point to a small set of generalised coordinates. The same exact analytical solutions of the notch tip asymptotic field derived for a symmetrical notch case can be used as GIFs when the notch is non-symmetrical. However, appropriate local coordinate transformation in the singular region is required to obtain the correct global stiffness matrix. Neither post-processing technique to extract SIFs nor special singular elements to model the singular region are required. Any conventional finite elements can be used to model the singular region. The SIFs are directly computed because of the use of exact analytical solutions as GIFs whose coefficients (generalised coordinates) are the unknowns in the singular region. To demonstrate the accuracy and efficiency of the FFEM to compute the SIFs and model the singularity at a notch tip of non-symmetrical configurations of notched plates, various numerical examples are presented and results are validated via available published data.

Particle Clustering to Improve Omnidirectional Localization in Outdoor Environments

Monte Carlo Localization (MCL) is a common method for self-localization of a mobile robot under the assumption that a map of the environment is available. In addition to laser scanners and sonar sensors, localization approaches using vision sensors have also been recently developed with good results. In this paper we present two variations to improve the standard implementation of the MCL algorithm. The first change consists in a new strategy for the generation of particles, both at the initialization and at the resampling stage, which tries to generate new particles near the position of images in the learning dataset or in the neighborhood of particles with higher weights in the previous estimate, respectively. The second variation is related to a new approach to the estimate of the robot position, now based on two steps: clustering of particles and taking as estimate of robot position the center of the cluster, computed as a weighted sum of particle weights, with higher weight. The improved MCL algorithm described in this paper is compared with the standard MCL algorithm in terms of localization accuracy. In particular, tests were performed using local feature matching of omnidirectional images implemented on a real robot system operating in large outdoor environments with high dynamic content. Obtained results show that the localization accuracy of the improved MCL algorithm is more than twice that of the standard MCL algorithm.

An Approach to Determine the Test Intervals for CBM

In this paper, reduction factor, which describes the degree of service age reduction resulting from the preventive maintenance, is introduced into a condition-based maintenance strategy. The model determining the sequential test intervals is formulated under the constraint that the probability that the failure has not test successfully within each test interval should be less than a fixed threshold. The failure risk of deteriorating system can be reduced via shortening test interval. The effectiveness of the presented methods is illustrated via a numerical case.

Possibility-Based Multidisciplinary Design Optimization in the Framework of Sequential Optimization and Reliability Assessment

Reliability Based Multidisciplinary Design Optimization (RBMDO) has received increasing attention to reach high reliability and safety in complex and coupled systems. In early design of such systems, however, information is often not sufficient to construct the precise probabilistic distributions required by the RBMDO and consequently RBMDO can not be carried out effectively. The present work proposes a method of Possibility Based Multidisciplinary Design Optimization (PBMDO) within the framework of the Sequential Optimization and Reliability Assessment (PBMDO-SORA). The proposed method enables designers to solve MDO problems without sufficient information on the uncertainties associated with variables, and also to efficiently decrease the computational demand. The efficiency of the proposed method is illustrated with an engineering design.

Autonomous Robotic Vehicle (Robicle) With Ambient Intelligence

Magnetic sensing is a reliable technology that has been developed for the purposed of position measurement and guidance, especially for applications in autonomous robotic vehicles. To calculate a position of a magnetic guidance road, it should be estimated in real-time. While the capability of a microprocessor and memory spaces have the limitation in implementation. To solve the above problems, this paper proposes a new structure of the magnetic sensors included a vertical magnetic field. The proposed method uses the linear region of the sensor output, and position determination using a simple equation with a microcontroller. The position sensing technique was implemented in the guidance of autonomous vehicle. The test results show that position sensing can be useful for an autonomous robotic vehicle.

Automatic Source Code Generator Based on AUTOSAR RTE for Vehicular Applications

We propose a new approach to an automatic source code generator for the AUTOSAR-based vehicular software. The growing number of electrics/electronics software in vehicle systems makes more and more necessary the increasing demands. For example, it needs the essential requirements such as ensuring reliability, low production cost, coping with limited resources, and so on. Recently, there have been relative studies that point to this issue. An AUTOSAR development partnership is such a case. AUTOSAR is a standardized automotive software architecture which is an alliance of OEM and supplier. Now, the focus is mainly directed at a source code generator that deals with the AUTOSAR standard concept. In this paper, we present a novel source code generator which is based on the AUTOSAR software platform. The experimental process is presented to functionally verify the module, and structurally verify the generated source code.

Design of “Figure-8” Spherical Motion Flapping Wing for Miniature UAV

Hummingbirds and some insects exhibit a “Figure-8” flapping motion, which allows them to undergo variety of maneuvers including hovering. It is therefore desirable to have miniature air vehicle (FWMAV) with this wing motion. This paper presents a design of a flapping-wing for FWMAV that can mimic “Figure-8” motion using a spherical four bar mechanism. In the proposed design, the wing is attached to a coupler point on the mechanism, which is driven by a DC servo motor. A prototype is fabricated to verify that the design objectives are met. Experimental testing was conducted to determine the validity of the design. The results indicate good correlation between model and experimental prototype.