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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...
This paper presents an embedded vision system based on reconfigurable hardware (FPGA) and two CMOS cameras to perform stereo image processing and 3D mapping for autonomous navigation. We propose an EKF based visual SLAM and sparse feature detectors to achieve 6D localization of the vehicle in non flat scenarios. The system can operate regardless of the odometry information from the vehicle since visual...
Geolocation of a ground object or target of interest from live video is a common task required of small and micro unmanned aerial vehicles (SUAVs and MAVs) in surveillance and rescue applications. However, such vehicles commonly carry low-cost and light-weight sensors providing poor bandwidth and accuracy whose contribution to observations is nonlinear, resulting in poor geolocation performance by...
Accurate and reliable vehicle localization is a key component to numerous applications, including active vehicle safety systems, real time estimation of traffic conditions, and high occupancy tolling. Up to now, most of the localization techniques rely on a given set of sensors embedded in a single vehicle. In this paper, we survey the issues considered in designing collaborative methods for localizing...
One of the most important tacks for tracking and trajectory planning is how to represent suitably objects, evolving in complex environments (for example urban environment), in which different objects (pedestrians, bikes, vehicles) move unpredictably and close to each other. In the framework of the development of a multiple objects tracking system using multisensor fusion, this paper presents an oriented...
Tracking reentry vehicle with strong maneuvers on-line is a challenging task. The key is to develop suitable dynamic models and estimation methods. Two kinds of modeling methods are discussed for reentry tracking, and the unscented filter (UKF) is introduced to the nonlinear tracking system. To reduce the computational load, three simplifications of UKF are developed. Furthermore, the feasibility...
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