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The progress of Underwater Swarm Sensor Networks (USSNs) has required the development of new approaches and understanding to short-range mobile acoustic underwater communication. This communication is essential in USSN to coordinate the manoeuvring of the closely operating vehicles as well as to transmit data within the swarm to gain benefits of operating as a team. Implementation of swarms of vehicles...
A precise position and attitude information is essential for autonomous driving of any vehicle. Low-cost GNSS receivers and antennas can provide a precise attitude and drift-free position information. However, severe code multipath, frequent half cycle slips and losses of lock might temporarily reduce the accuracy. Inertial sensors are robust to GNSS signal interruption and very precise over short...
An integrated navigation method for land vehicle is researched in this paper, which is based on SINS, geomagnetic matching and barometric altimeter. Horizontal position output from geomagnetic matching, altitude output from barometric altimeter and corresponding outputs from SINS are taken to construct the measurement. Fuzzy self-adaptive kalman filtering algorithm is adopted in the design of integrated...
This study presents an innovative approach to detect drowsiness by using photoplethysmography signals which is easily acquirable with non-invasive techniques. Drowsiness detection based on biological signals is being employed in precautionary personal safety. Autonomous Nervous System (ANS) activity can be measured non-invasively from the Pulse Rate Variability (PRV) signal obtained from photoplethysmography...
This paper presents a rapid edge detection method for vehicle using the two-dimensional cellular neural network (CNN). In the method, two adaptive templates for edge detection are experimentally designed, and background noise elimination is also concerned. Finally, the performance of the proposed CNN detector is evaluated on different vehicle images, and it is also compared with some other edge detectors...
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...
License plate recognition (LPR) plays a major role in this busy world, as the number of vehicles increases day by day, theft of vehicles, breaking traffic rules, entering restricted area are also increases linearly, so to block this act license plate recognition system is designed. License Plate Recognition systems basically consist of 3 main processing steps such as: Detection of number plate, Segmentation...
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 paper presents a novel design of kinematics-based observer for vehicle sideslip angle estimation. A parameter-varying model is firstly obtained by regarding the measured yaw rate as a varying parameter. A yaw rate scheduled parameter-varying observer is then constructed using the measured yaw rate and accelerations, and is designed to be robust against the measurement noises. The conditions for...
A high-dimensional Simultaneous Localization and Mapping (SLAM) algorithm is presented that replaces the particles in FastSLAM with individual Gaussians. In addition, the high-dimensional vehicle state is partitioned into linear and nonlinear parts and the nonlinear part is approximated by a mixture of Gaussians of which the means and covariances are propagated and updated using sparse grid quadrature...
Accurate and robust environment perception is a prerequisite for advanced driver assistance systems such as parking assistance, collision avoidance or night vision systems but also for robot navigation. In this context, occupancy grid mapping is a common way to represent the static car surroundings perceived by radar, laser or camera sensors. This work focuses on the challenges of nighttime grid mapping...
Traveling with children in tow can pose a serious distraction to the driver, effectively drawing much of the necessary attention away from the road and causing a disruption in normal driving patterns. In this paper we investigate the driver's capacity to operate a vehicle safely when being exposed to a noise stimulus, specifically in the form of a crying baby for an extended period of time. For this...
A robust method to estimate tire forces for a passenger vehicle with the Unscented Kalman Filter (UKF) is provided. Only standard vehicle sensors were used and no a priori knowledge of tire and road properties was required. The estimator uses the bicycle model and a random walk tire force model. The tire force estimates were compared to a CarSim reference model for combined slip maneuvers. The results...
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...
In this paper, the distributed second-order tracking control problem of a multi-vehicle system is investigated over a directed connection topology. It is supposed that each vehicle can only obtain the position measurements of itself and its neighbors in a noisy environment. The problem is solved by embedding a finite-time convergent estimator in each vehicle and then combining it with a linear or...
This paper investigates the impact of tele-operation on energy consumption of a small unmanned ground vehicle (UGV). Using statistical response surface analyses, it is shown that factors such as velocity, stop-and-go operations, human operator delay and aggressiveness, and their interactions significantly increase the energy requirements in a typical mission. We investigate the effect of velocity...
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...
Obstacle avoidance is a key feature for automotive navigation that requires an accurate representation of the environment. In the field of visual perception this task has often been addressed with stereo algorithms that try to obtain a depth map of the environment via disparity calculations on a single pair of images. These algorithms do not exploit that especially in automotive scenarios the fields...
The main contribution of this paper is a novel planning algorithm that, starting from a probabilistic roadmap, efficiently constructs an expanded graph used to search for the optimal solution of a multi-objective problem. The primary cost is the shortest path from start to goal and the secondary cost is related to the state estimation error covariance. This needs to be optimized as we assume the navigation...
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