Harbin Engineering University

About: Harbin Engineering University is a education organization based out in Harbin, Heilongjiang, China. It is known for research contribution in the topics: Control theory & Computer science. The organization has 31149 authors who have published 27940 publications receiving 276787 citations. The organization is also known as: HEU.

Preparation and up-conversion luminescence of hollow La2O3:Ln (Ln = Yb/Er, Yb/Ho) microspheres.

Abstract: Hollow La(2)O(3):Ln (Ln = Yb/Er, Yb/Ho) microspheres with up-conversion (UC) luminescence properties were successfully synthesized via a facile sacrificial template method by employing carbon spheres as hard templates followed by a subsequent heating process. The structure, morphology, formation process, and fluorescent properties are well investigated by various techniques. The results indicate that the hollow La(2)O(3):Ln microspheres can be well indexed to the hexagonal La(2)O(3) phase. The hollow La(2)O(3):Ln microspheres with uniform diameter of about 270 nm maintain the spherical morphology and good dispersion of the carbon spheres template. The shell of the hollow microspheres consists of numerous nanocrystals with the thickness of approximately 40 nm. Moreover, the possible formation mechanism of evolution from the carbon spheres to the amorphous precursor and to the final hollow La(2)O(3):Ln microspheres has also been proposed. The Yb/Er and Yb/Ho codoped La(2)O(3) hollow spheres exhibit bright up-conversion luminescence with different colors derived from different activators under the 980 nm NIR laser excitation. Furthermore, the doping concentration of the Yb(3+) is optimized under fixed concentration of Er(3+)/Ho(3+). This material may find potential applications in drug delivery, hydrogen and Li ion storage, and luminescent displays based on the uniform hollow structure, dimension, and UC luminescence properties.

Integrated Indoor Navigation System for Ground Vehicles With Automatic 3-D Alignment and Position Initialization

Abstract: This paper introduces an autonomous integrated indoor navigation system for ground vehicles that fuses inertial sensors, light detection and ranging (LiDAR) sensors, received signal strength (RSS) observations in wireless local area networks (WLANs), odometry, and predefined occupancy floor maps. This paper proposes a solution for the problem of automatic self-alignment and position initialization indoors under the absence of an absolute navigation system such as Global Navigation Satellite Systems (GNSS). The initial tilt angles (roll and pitch) are estimated by an extended Kalman filter (EKF) that uses two horizontal accelerometers as measurements. The initial position and heading estimation is performed using a subimage matching algorithm based on normalized cross-correlation between projected 2-D LiDAR scans and an occupancy floor map of the environment. The ambiguities in position/heading initialization are resolved using RSS. The proposed position/heading estimation module is also utilized in navigation mode as a source of absolute position/heading updates to EKF for enhanced observability. The state predictor is an enhanced 3-D inertial navigation system that utilizes low-cost microelectromechanical system (MEMS)-based reduced inertial sensor set aided by vehicle odometry. In navigation mode, LiDAR scans are used to estimate the vehicle's relative motions using an inertial-aided iterative closest point algorithm. To fuse all available measurements, a multirate multimode EKF design is proposed to correct navigation states and estimate sensor biases. The developed system was tested under a real indoor office environment covered by an IEEE 802.11 WLAN on a mobile robot platform equipped with MEMS inertial sensors, a WLAN interface, a 2-D LiDAR scanner, and a quadrature encoder. Results demonstrated the capabilities of the self-alignment and initialization module and showed average submeter-level positioning accuracy.