Sharif Digital Repository

In-motion alignment of a strapdown inertial navigation system, during slow maneuvers, is studied. Terrestrial velocity is fed back to the navigation system to estimate and compensate for the navigation errors. Observability of the errors is analyzed since the integrated navigation system is not fully observable. Then, the accuracy bounds of the navigation system in different motion scenarios are obtained analytically. Also, in order to minimize the errors of the navigation system, special maneuvers are designed based on the analytical derivations. The analytical results, obtained using the linearized error model, are verified through nonlinear simulation of different maneuvering and... 

Underwater navigation is generally accomplished through the data fusion of INS (Inertial Navigation System) and auxiliary sensors such as DVL (Doppler Velocity Logger) sensor. However, because of the possibility of DVL outage, alternative low-cost solutions are attractive. Among these, one is using vehicle kinetic model information extracted by the Newton-Euler equation to improve INS performance, which is called model-aided navigation. In this paper, only the vehicle translational motion dynamics are used to replace DVL in underwater navigation in DVL outage. The vehicle 3D translational dynamics has been obtained by using general Newton-Euler equations. Integrating these dynamics leads to... 

In this research, Model Aided Inertial Navigation (MAIN) is used during the automatic landing of an Unmanned Aerial Vehicle (UAV). A new MAIN algorithm is proposed which is fast and accurate enough to be used in this phase. In this algorithm, the six Degree of Freedom (6DoF) flight simulation of the UAV is integrated with the Inertial Navigation System (INS) such that the 6DoF model acts as an aiding system for the INS. In the last parts of the landing phase, when the UAV flies in proximity of the ground surface, the proposed integrated navigation system can estimate the altitude of UAV utilizing the “ground effect” phenomenon. Therefore, the method does not have the drawbacks of active... 

Underwater navigation is generally accomplished through the data fusion of INS (Inertial Navigation System) and auxiliary sensors such as DVL (Doppler Velocity Logger) sensor. However, because of the possibility of DVL outage, alternative low-cost solutions are attractive. Among these, one is using vehicle kinetic model information extracted by the Newton-Euler equation to improve INS performance, which is called model-aided navigation. In this paper, only the vehicle translational motion dynamics are used to replace DVL in underwater navigation in DVL outage. The vehicle 3D translational dynamics has been obtained by using general Newton-Euler equations. Integrating these dynamics leads to... 

This article aims to compensate the velocity and position errors that exist when the star sensor starts to work in a strapdown inertial navigation system aided by celestial navigation. These systems are integrated via unscented Kalman filter to estimate the current attitude and the gyros fixed bias, precisely. Since an accurate integration is desired, the nonlinear attitude equations are utilized in filter and these equations are propagated through a precise discretization method. Then, implementing the back-propagation and smoothing techniques, the initial attitude and the accelerometers fixed bias are also estimated. Finally, carrying out a parallel navigation, the velocity and position... 

Robot navigation is a challenging problem in robotics, which involves determining of robot positioning relative to objects in the environment, and also the mobility of robot through obstacles without colliding into them. The former is known as localization, while the latter is called motion planning. This paper introduces a roadmap method for solving motion planning problem in a dynamic environment based on Generalized Voronoi Diagram (GVD). The efficiency of the proceeding work is verified by examining it in a sample home environment. © 2008 Springer-Verlag  

In this paper, a new approach for behavior based architecture in mobile robot navigation in unknown environments is presented. In this approach, the general actions of a mobile robot are classified into three thoroughly separated tasks. Then, an individual fuzzy controller is designed and implemented for each task (behavior). Finally, a behavior selector is designed to switch between the robot tasks (behavior patterns) and manage all separated fuzzy controllers to navigate a mobile robot in a fully unknown environment. Another case considered in this paper is to test and examine the proposed algorithm in an environment including the static and dynamic (moving) obstacles. The most difficult... 

In this paper, a novel algorithm for correcting the error of attitude in inertial navigation systems is introduced. Since the oftenly used differential equations of the navigation errors show the small rotation angles instead of the error of Euler angles, the nonlinear equation between the small rotation angles and the error of Euler angles, are derived. To obtain an approximative solution for the derived equations, third order multiplication of the small rotation angles are ignored and error of Euler angles are expressed explicitly as functions of the Euler angles and the small rotation angles. Based on the obtained solution, a new algorithm for attitude correction in inertial navigation is... 

This paper introduces a new method for improving the inertial navigation system errors using information provided by the camera. An unscented Kalman filter is used for integrating the inertial measurement unit data with the features’ constraints extracted from the camera’s image. The constraints, in our approach, comprise epipolar geometry of two consecutive images with more than 65% coverage. Tracking down a known feature in two consecutive images results in emergence of stochastic epipolar constraint. It emerges in the form of an implicit measurement equation of the Kalman filter. Correctly matching features of the two images is necessary for reducing the navigation system errors because... 

INS-DVL integration is a common method for underwater navigation. However, inherent errors of sensors, especially in MEMS IMUs, lead to inaccuracies in estimating the position and attitude. In this paper, dynamic motion model of AUV is used to improve MEMS INS-DVL navigation. In this method, which is called model-aided or model-based navigation, the information of the kinetic model of the vehicle (obtained from Newton-Euler equations) is used to improve the navigation performance. Previous model-aided navigation studies about AUVs have been focused on the translational dynamic model of vehicles. As the best of our knowledge, this paper is the first one which suggests using a rotational... 

In this paper a technique for autonomous navigation of mobile robots is presented. The most important advantage of this method is to ignore the physical model of the robot and that the robot model is considered as an unknown but predictable system. This approach can be executed in environments which robot navigation is done using global sensors e.g. a camera installed in the environment to sense and control the robot and also every feedback system which is able to measure the velocity of the robot can be used for this technique. In this approach, the well-known fuzzy method, Takagi-Sugeno, has been applied to estimate the dynamic model of robot. Our technique has been applied successfully in... 

The aim of this paper is to design an inertial navigation system (INS) for use in a geometry pipe inspection gauge, capable of measuring pipeline movements and producing the line's 3D map with a reasonable accuracy. A suitable reference path was generated as a design platform. Solving the navigation equations and compensating for the errors, by using extended Kaiman filter (EKF) approach, the INS path was generated and its position errors in all three directions were considered. Divergence problems due to far apart GPS position observations, was overcome by defining suitable threshold for the variances of the estimated errors. Copyright © 2007 by ASME  

Satellite-based navigation has rapidly evolved into an efficient tool extensively used in a wide variety of civilian applications covering numerous modes of transportation, communication, administration, geodesy, agriculture, etc. The current systems globally available are the US Global Positioning System (GPS) and the conceptually very similar Russian Global Navigation Satellite System (GLONASS). The European Union (EU) has also decided to press ahead with plans to develop Galileo system, a European version of the Global Positioning System (GPS) after the system definition during 1999/2000. The development phase of Galileo is expected to run from 2002 to 2005 with a deployment phase,... 

Future micro aerial vehicles (MAVs) will have missions occur within and around buildings. This paper describes a vision-based navigation of a very light fixed wing aircraft in flight between obstacles. A geometrical method has been proposed to model the optical flow measurement process using the camera perspective model, the flight equations and the scene geometry. The optical flow information are used to detect the obstacles and perform turn maneuvers based on the balance strategy. The flight of an aircraft in a corridor which encounters a 3-way junction was simulated. The effect of the ways width ratio and the cameras' field of view angles on the aircraft navigation behavior at the... 

The problem of gyrocompassing using inertial sensors, i.e., gyros and accelerometers, is addressed. North finding, with an order of accuracy of one arc-min, is not only required for the initial alignment of inertial navigation systems, but also has a critical role to play in the guidance and navigation of ships that navigate for long periods of time. In this work, after extracting the error model of an inertial navigation system and augmenting it with the error model of inertial sensors, a processing algorithm based on the Kalman filter is designed and simulated to process the navigation system velocity error, and to estimate and correct tilt and heading errors along with gyro drifts and... 

Nowadays, Autonomous Underwater Vehicles (AUV) are used in environmental studies, ocean floor mapping, and measuring water properties. Navigation of these vehicles is one of the most challenging issues due to the unavailability of global positioning system (GPS) signal underwater. Inertial navigation is a method commonly used for underwater navigation. If a low-cost Inertial Measurement Unit (IMU) is used, navigation quality will decline rapidly due to sensor inherent error. Although using a Doppler Velocity Log (DVL) speedometer sensor helps limit this error to some extent, it does not yield acceptable accuracy in low-cost IMUs. Filtering the gyro based on the AUV rotational dynamics model...