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We demonstrate trajectory control of the tip of an inverted pendulum atop a small unmanned aerial vehicle. In this paper we discuss how exploiting the differential flatness of combined systems provides a realization of adequate control. A differential flatness controller is derived for trajectory control of a pendulum tip. Simulation results are presented for tip trajectory tracking with and without...
Novel sensor fusion architecture is proposed to provide complete navigational solution for micro aerial vehicles (MAV) using low cost sensors and micro controller. The approach uses a nonlinear complementary filter (NCF) to estimate direction cosine matrix (DCM), the estimated attitude and heading from DCM are used in turn to predict MAV position in North and East direction and a two state extended...
This paper presents the development of a state observer for a 2-axle railway vehicle with solid axle wheelsets. A plan view model of the vehicle is presented and a Kalman filter is developed to estimate 18 states from 8 inertial measurements. The required measurements are the lateral acceleration and yaw velocity of the vehicle body and the same measurements plus the roll velocity for the two wheelsets,...
The vehicle state is of significant to examine and control vehicle performance. But some vehicle states such as vehicle velocity and side slip angle which are vital to active safety application of vehicle can not be measured directly and must be estimated instead. In this paper, a Cubature Kalman Filter (CKF) based algorithm for estimation vehicle velocity, yaw rate and side slip angle using steering...
This paper describes a self-balancing mobile robot and their principal features as materials of construction, instrumentation, data communication and control. This kind of robots are an excellent platform for testing different techniques of control due to characteristics of the system (unstable, underactuated). The tilt measurement by means of an Accelerometer-Gyro pair to control a two-wheeled, self-balancing...
Precision of vehicle navigation can be significantly improved by adding motion constraints. How to model multi-motion constraints and choose appropriate motion constraint according to vehicle mobility need to be solved in practical usage. This article established a unified state error model and deduced a measurement model for several common vehicle motion constraints, like ZUPT, MCA and HDR, used...
This paper presents a mathematical model for car-to-car (C2C) visible light communications (VLC) that aims to predict the system performance under different communication geometries. A market-weighted headlamp beam pattern model is employed. We consider both the line-of-sight (LOS) and non-line-of-sight (NLOS) links, and outline the relationship between the communication distance, the system bit error...
To reduce the effect of changes in gravity field and radius on Aerospace Vehicles navigation system, an inertial navigation algorithm in launch inertial coordinate for ASV is studied in this paper firstly. To overcome the poor performance of Kalman filter in uncertain environment, an extended H∞ filtering algorithm is designed secondly. Combining the advantages of launch inertial coordinate and H∞...
This research proposes a novel scheme for vision-aided inertial navigation based on planar homography. By exploiting the multiplicative group property of homography matrices, extended Kalman filter-based vision aiding is formulated with a measurement model of the group difference between image-estimated and navigation homographies. A simple compensation for depth distortion of the homography matrix...
This paper presents the Optimized Kalman Particle Swarm (OKPS) filter. This filter is a new robust data fusion approach adapted for ego-vehicle localization in degraded signal conditions. The OKPS is the improved version of the hybridization of the Particle Filter (PF) by Particle Swarm Optimization notions (PSO). Taking also some features from the Extended Kalman filter (EKF), the OKPS is designed...
Intrinsic calibration, i.e. finding the mapping between a camera's image positions and corresponding view rays, is a cumbersome, yet unavoidable task in order to accurately generate and interpret results from many kinds of image processing algorithms. We address this problem in the context of vehicle-mounted cameras with arbitrary fields of view with applications in advanced driver assistance systems...
This paper presents a chance constrained approach to extracting linear models from reference data to be used in subsequence identification or pattern matching. Due to the ordered nature of time series data, the extracted models are sequential, with feasible domains separated by transition points. In a sequence of models, a transition point is defined as the point where one model is invalid and the...
Misalignment angles estimation of strapdown inertial navigation system (INS) using global positioning system (GPS) data is highly affected by measurement noises, especially with noises displaying time varying statistical properties. Hence, adaptive filtering approach is recommended for the purpose of improving the accuracy of in-motion alignment. In this paper, a simplified form of Celso's adaptive...
We present an iterative learning scheme for improving the performance of highly dynamic open-loop maneuvers with quadrocopters. A probabilistic estimate of the state deviation at the end of the maneuver is obtained by fusing two data sources that are available on-board: 1) an inertial measurement unit, and 2) control inputs from an external pilot that performs a recovery after the open-loop maneuver...
For the shortages of the existing vehicle positioning technologies, a method combining radio frequency identification (RFID) positioning technology with extended kalman filter (EKF) algorithm to realize the vehicle positioning in urban complex environments is proposed. The preliminary noise-contained position information based on RFID positioning is fused with steering wheel angle and wheel speed...
This paper proposes a method for using a forward-looking monocular camera along with previewed road geometry from a high-fidelity, low-dimensional map to estimate lateral planar vehicle states by measuring the vehicle's temporally anticipated reference trajectory. Theoretical estimator performance from a steady-state Kalman Filter implementation of the estimation framework is calculated for various...
The sound radiation from vehicles moving on city road with T intersection is considered. The solution of problem is found on the base of superposition of the solutions with taking into account of wind effect in acoustic field for the cases of vehicles move along straight roads and roads with the right-angle bend. The numerical analysis of traffic noise characteristics is carried out for the T junction...
This paper describes a novel method for the location of road vehicles using vehicle pitch data obtained from on-board sensors. The method encodes the road map data using linear dynamical models, and then, during travel, identifies the vehicle location through continuous validation of the previously obtained linear models. The approach presented has several advantages over previous approaches in the...
One-way-travel-time (OWTT) acoustic ranging has received considerable attention as improvements to acoustic modems and electronic clocks have made it a feasible navigation tool. This paper reports the results of simulations investigating the effect of utilizing inter-vehicle ranging for autonomous underwater vehicle (AUV) navigation. In these simulations, a fleet of AUVs operates in shallow water...
Ego-localization is a key issue for most autonomous robots and vehicles. Indeed, the ability to take a proper decision (avoidance, path-finding, etc.) relies on the knowledge of one's particular environment on one hand and on its relative positioning in this environment on the other hand. As such, this issue has been addressed multiple times in the past few years. This work extends a multi-sensor...
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