Luo Yuan

Intelligent wheelchair system based on sEMG and head gesture

Abstract Because the single channel surface electromyographic (sEMG) signals easily caused a complex operation during the real-time operation, an intelligent wheelchair system based on sEMG and head gesture was proposed in this paper. A distributed parallelly decision fusion algorithm fused classification results of the two signals to form a final judgment. After sEMG was decomposed by wavelet packet, feature information of some subspace was weaken, because subspace dimension was very large. To solve the problem, the paper proposed an improved wavelet packet decomposition algorithm, which extracted sample entropy from four subspaces of improved wavelet packet decomposition and took it as the feature information. Experimental results show that the intelligent wheelchair system based on sEMG and head gesture has not only a simple operation and shorter operating time, but also a better stability and security.

Design of a modified circular-cut multiband fractal antenna

Abstract This paper presents a modified circular-cut multiband fractal antenna with good radiation patterns designed for digital cellular system (DCS), personal communication system (PCS), 2.4/5.2/5.8 GHz wireless local area networks (WLAN) and 2.5/3.5/5.5 GHz worldwide interoperability for microwave access (WiMAX) applications simultaneously. Originally, the modified circular monopole antenna is designed to resonate at around 2.1 GHz and 3.6 GHz. After subtracting the circular iterative tree fractal structure, it can produce three other resonances at around 5.6 GHz, 6.47 GHz and 7.89 GHz. Besides, as the number of iterations increases, not only do the new frequency bands appear (it demonstrates the good self-similarity property of the proposed antenna), but also the operating bands shift from high frequency to low frequency (it shows the well space filling property). Furthermore, the proposed antenna owns a compact structure, which can achieve the 5.28 dBi of relative high gain. And the measured results are basically accordant to simulated results, which proves the effectiveness of the proposed antenna.

Improved Rao-Blackwellized H∞ filter based mobile robot SLAM

Abstract For the problems of estimation accuracy, inconsistencies and robustness in mobile robot simultaneous localization and mapping (SLAM), a novel SLAM based on improved Rao-Blackwellized H∞ particle filter (IRBHF-SLAM) algorithm is proposed. The iterated unscented H∞ filter (IUHF) is utilized to accurately calculate the importance density function, repeatedly correcting the state mean and the covariance matrix by the iterative update method. The laser sensors observation information is introduced into sequential importance sampling routine. It can avoid the calculation of Jacobian matrix and linearization error accumulation; meanwhile, the robustness of the algorithm is enhanced. IRBHF-SLAM is compared with FastSLAM2.0 and the unscented FastSLAM (UFastSLAM) under different noises in simulation experiments. Results show the algorithm can improve the estimation accuracy and stability. The improved approach, based on the robot operation system (ROS), runs on the Pioneer3-DX robot equipped with a HOKUYO URG-04LX (URG) laser range finder. Experimental results show the improved algorithm can reduce the required number of particles and the operating time; and create online 2 dimensional (2-D) grid-map with high precision in different environments.