Mohammad Reza Asharif

Pseudo information measure: a new concept for extension of Bayesian fusion in robotic map building

Abstract A new concept named pseudo information measure is introduced. By this measure, Bayesian fusion of independent sources of information is extended to a wide range of possible formulations and some new fusion formulas are calculated. The coincidence between the performance of the proposed method of fusion with the expected results and output sensitivity of the fusion process are discussed. Also, we have discussed the resulting flexibility for map building applications. Map building by using the proposed fusion formulas has been simulated for a cylindrical robot with eight ultrasonic sensors and implemented on Khepera robot. The resulting maps have been fed to an improved version of A* path planning for comparative purposes. For the resulting routes, two factors have been considered and calculated: length and the least distance to obstacles. The results show that the maps of the environment that are generated by using the proposed fusion formulas are more informative. In addition, more appropriate routes are achieved. Based on the selected function, there is a trade-off between the length of the resulting routes and their safety. This flexibility lets us choose the right fusion function for different map building applications.

Sensor fusion for ultrasonic and laser arrays in mobile robotics: a comparative study of fuzzy, Dempster and Bayesian approaches

In any autonomous mobile robot, if not the most, one important issue to be designed and implemented on the robot, is environment perception and its role in autonomous navigation. There are many grid-based and topological methods for environment mapping. Among the grid-based methods the main difference is about the method of data integration that is applied to mapping. In this paper, three different approaches are formulated to perform sensor data integration in the process of generation of a generalized version of occupancy grids map of the environment. The methods are formulated based on Bayesian, Fuzzy and Dempster-Shafer approaches to data fusion/integration. Although, they are famous for data fusion applications, in this research work they have been applied, formulated and simulated to solve a unique problem: map building for the same mobile robot, equipped with 8 Polaroid ultrasonic range finder sensors and operating in the same environment. The simulation results are applied for comparative study of the merits of the methods and their applicability in the map building and environment perception for autonomous mobile robots. They show that the Bayesian approach gives more appropriate maps, by which, A* path planning algorithm leads to shorter and safer routes for the mobile robot to navigate.

Expanded CLMS algorithm for double-talk echo cancelling

The correlation LMS (CLMS) algorithm has been proposed to solve the double-talk problem in echo cancelling for a teleconference system. This algorithm has the unique characteristic that it uses a correlation function of the input signals instead of the input signals itself. But this algorithm does not have a sufficient performance yet. Therefore, we propose an expanded CLMS algorithm in which the MSE is obtained for the sum of lagged squared errors. The proposed algorithm obtains a better performance than the CLMS algorithm in the double-talk situation.

Improved Pose Estimation for Mobile Robots by Fusion of Odometry Data and Environment Map

This paper proposes a new approach for calibration of dead reckoning process. Using the well-known UMBmark (University of Michigan Benchmark) is not sufficient for a desirable calibration of dead reckoning. Besides, existing calibration methods, usually require explicit measurement of actual motion of the robot. Some recent methods, use the smart encoder trailer or long range finder sensors such as ultrasonic or laser range finders for automatic calibration. Manual measurement is necessary in the case of the robots that are not equipped with long range detectors or such smart encoder trailer. Our proposed approach, uses an environment map that is created by fusion of proximity data, in order to calibrate the odometry error automatically. In the new approach, the systematic part of the error is adaptively estimated and compensated by an efficient and incremental maximum likelihood algorithm. Actually, environment map data are fused with the odometry and current sensory data in order to acquire the maximum likelihood estimation. The advantages of the proposed approach are demonstrated in some experiments with Khepera robot. It is shown that the amount of pose estimation error is reduced by a percentage of more than 80%.

Design of echo canceler with frequency domain ECLMS algorithm

The correlation LMS (CLMS) algorithm and its extended version (ECLMS) have been proposed to solve the double-talk problem in the echo canceling for the teleconference system by authors previously. However, the computational load of the ECLMS is too large to be implemented. Here, we propose a new fast implementation of the ECLMS algorithm using frequency domain based on time lag of the correlation function. Also, we defined initialization and normalization methods. The performance has been verified by computer simulation using a speech signal. The computational complexity of the proposed algorithm is reduced to only 2.7% of the ECLMS algorithm.

A theoretical discussion on the foundation of Stone’s blind source separation

This paper discusses the theoretical foundation of Stone’s BSS (Stone in Neural Comput 13:1559–1574, 2001; Stone in Independent Component Analysis: A Tutorial Introduction, A Bradford Book, London, 2004), and it proposes a novel BSS approach based on second-order statistics of the responses of two different linear filters to source signals. The proposed approach which includes Stone’s BSS as a special case helps us to understand how generalized eigenvalue decomposition (GEVD) concludes separating vectors in Stone’s BSS. It obtains the separating vectors by simultaneous diagonalization of covariance matrices of two different linear filters responses to the mixtures. The two employed linear filters are selected dependent on source signals structures under the assumption that they have different responses to source signals. Here, two FIR filters with coefficients selected in an opposite probabilistic way have been suggested for the proposed BSS. The proposed BSS method has been compared with Stone’s BSS, SOBI and AMUSE over speech and image mixtures in different noise levels.

Fast communication: Adaptive step-size NCLMS algorithm for double-talk echo canceling

In systems, such as hands-free mobile telephony, voice over internet protocol (VoIP), voice control, hearing aids, public address and teleconferencing, we are still faced with echo problem. Adaptive digital filters have been vastly used for the echo canceling by estimating the reverberation room impulse response. When a strength near-end talker (NET) signal exists, the adaptation process of the conventional algorithms misleads. In this paper, based on the correlation functions, we introduce a new algorithm named as adaptive step-size normalized correlation-based least mean square (ASNCLMS) algorithm, which is robust even in the presence of NET signal. This algorithm does not freeze the adaptation process during double-talk (DT) mode. Computer simulations, which prove the robustness of this algorithm, are also presented.

Adaptive filter by using proportionate frequency domain extended correlation LMS algorithm in the double-talk condition

Echo path estimation in echo canceling for teleconference system is a problem in double-talk condition. The correlation function based algorithms were defined by the authors to solve this problem. In this paper, in order to improve the convergence speed of correlation function based algorithm, we propose a new modified proportionate step-size adaptation method, and then implement it into frequency domain extended correlation LMS algorithm (FECLMS). The new algorithm is called proportionate frequency domain extended correlation LMS algorithm (PFECLMS). The computer simulation results support the theoretical findings and verify the robustness of the proposed algorithm in the double-talk situation.

Perceptual Adaptation of Image Based on Chevreul–Mach Bands Visual Phenomenon

The perceptual adaptation of the image (PAI) is introduced by inspiration from Chevreul–Mach Bands (CMB) visual phenomenon. By boosting the CMB assisting illusory effect on boundaries of the regions, PAI adapts the image to the perception of the human visual system and thereof increases the quality of the image. PAI is proposed for application to standard images or the output of any image processing technique. For the implementation of the PAI on the image, an algorithm of morphological filters (MFs) is presented, which geometrically adds the model of CMB effect. Numerical evaluation by improvement ratios of four no-reference image quality assessment (NR-IQA) indexes approves PAI performance where it can be noticeably observed in visual comparisons. Furthermore, PAI is applied as a postprocessing block for classical morphological filtering, weighted morphological filtering, and median morphological filtering in cancelation of salt and pepper, Gaussian, and speckle noise from MRI images, where the above specified NR-IQA indexes validate it. PAI effect on image enhancement is benchmarked upon morphological image sharpening and high-boost filtering.

Analysis of Non-linear Adaptive Friction and Pitch Angle Control of Small-Scaled Wind Turbine System

The aim of this research is toanalyze the behavior of wind turbine system for passive and adaptive resistance non-linear control. In general, the wind turbine system is generating energy from the revolution of blades. The revolution of blades is depended on the velocity of wind. So, if we have strong wind then the revolution of blade is increased and in consequently more energy will generated. Therefore, usually the wind turbine systems are located in gale area in order to generate energy efficiency. However, there are limits of the revolution of blades or the angular velocity of blades. If the angular velocity exceeds the limit then wind turbine system may breakdown. Thus in this paper, in order to avoid the malfunction of wind turbine system, adaptive and passive non-linear control of resistance is considered. As consequences, the adaptive resistance has more stable and smooth angular velocity compare to passive resistance.