scholarly journals Particle Filter and Finite Impulse Response Filter Fusion and Hector SLAM to Improve the Performance of Robot Positioning

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Amin Bassiri ◽  
Mohammadreza Asghari Oskoei ◽  
Anahid Basiri
Keyword(s):  
Particle Filter ◽  
Impulse Response ◽  
Hybrid Algorithm ◽  
Finite Impulse Response ◽  
Sampling Rate ◽  
Position Estimation ◽  
Laser Sensor ◽  
Indoor Environments ◽  
Hybrid Filter ◽  
Signal Ratio

Indoor position estimation is essential for navigation; however, it is a challenging task mainly due to the indoor environments’ (a) high noise to signal ratio and (b) low sampling rate and (c) sudden changes to the environments. This paper uses a hybrid filter algorithm for the indoor positioning system for robot navigation integrating Particle Filter (PF) algorithm and Finite Impulse Response (FIR) filter algorithm to assure the continuity of the positioning solution. Additionally, the Hector Simultaneous Localisation and Mapping (Hector SLAM) algorithm is used to map the environment and improve the accuracy of the navigation. The paper implements the hybrid algorithm that uses the integrated PF, FIR, and Hector SLAM, using an embedded laser scanner sensor. The hybrid algorithm coupled with Hector SLAM is tested in several scenarios to evaluate the performance of the system, in terms of continuity and accuracy of the position estimation, and compares it with similar systems. The scenarios where the system is tested include reducing the laser sensor readings (low sampling rate), dynamic environments (change in the location of the obstacles), and the kidnapped robot situation. The results show that the system provides a significantly better accuracy and continuity of the position estimation in all scenarios, even in comparison with similar hybrid systems, except where there is a high and constant noise, where the performance of the hybrid filter and the simple PF seems almost the same.

scholarly journals Computing efficiency of the three-stage interpolated low pass filters

2018 ◽  
Vol 28 (4) ◽  
pp. 21-27
Author(s):  
I. S. Savinykh ◽  
D. A. Chemasov
Keyword(s):  
Impulse Response ◽  
Computational Efficiency ◽  
Finite Impulse Response ◽  
Sampling Rate ◽  
Efficiency Coefficient ◽  
Transition Band ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Low Pass ◽  
Low Pass Filters

Undoubted advantages of finite impulse response filters are their unconditional stability, the absence of limit cycles and the possibility of implementing a filter that does not introduce phase distortion. The disadvantage of such filters is the large cost required to compute the response. This paper considers three-stage interpolated finite impulse response low-pass filters. The maximum values of the interpolation factors are determined. Dependences of the coefficient of computational efficiency and the coefficient of increase in the registers of the three-stage interpolated low-pass filter on the values of the interpolation factors, the widths of the passband and the transition band are obtained. Relations for determining the optimal values of interpolation factors corresponding to the maximal value of computational efficiency coefficient are obtained. In addition, the dependencies of the maximum coefficient of computational efficiency and the optimal coefficient of increase in the registers of the three-stage interpolated low-pass filter on the widths of the passband and the transition band at the optimum values of the interpolation factors are obtained. Considered three-stage interpolated low-pass filters should be used in the case when the required stopband is significantly less than the sampling rate. In this case, three- stage interpolated filters require less computational resources for calculating the response than the two-stage interpolated filters or filter implemented by the transversal structure.

scholarly journals NANO-studio, the design environment of filter banks implemented in standard CMOS technology

2021 ◽  
Author(s):  
Andrzej Handkiewicz ◽  
Mariusz Naumowicz
Keyword(s):  
Impulse Response ◽  
Filter Banks ◽  
Finite Impulse Response ◽  
Infinite Impulse Response ◽  
Cmos Process ◽  
Digital Cmos ◽  
Additional Advantage ◽  
Analysis And Synthesis ◽  
Optimization Parameters ◽  
Synthesis Filter

AbstractThe paper presents a method of optimizing frequency characteristics of filter banks in terms of their implementation in digital CMOS technologies in nanoscale. Usability of such filters is demonstrated by frequency-interleaved (FI) analog-to-digital converters (ADC). An analysis filter present in these converters was designed in switched-current technique. However, due to huge technological pitch of standard digital CMOS process in nanoscale, its characteristics substantially deviate from the required ones. NANO-studio environment presented in the paper allows adjustment, with transistor channel sizes as optimization parameters. The same environment is used at designing a digital synthesis filter, whereas optimization parameters are input and output conductances, gyration transconductances and capacitances of a prototype circuit. Transition between analog s and digital z domains is done by means of bilinear transformation. Assuming a lossless gyrator-capacitor (gC) multiport network as a prototype circuit, both for analysis and synthesis filter banks in FI ADC, is an implementation of the strategy to design filters with low sensitivity to parameter changes. An additional advantage is designing the synthesis filter as stable infinite impulse response (IIR) instead of commonly used finite impulse response (FIR) filters. It provides several dozen-fold saving in the number of applied multipliers.. The analysis and synthesis filters in FI ADC are implemented as filter pairs. An additional example of three-filter bank demonstrates versatility of NANO-studio software.

scholarly journals CONCURRENT MAP BUILDING AND LOCALIZATION ON INDOOR DYNAMIC ENVIRONMENTS

2002 ◽  
Vol 16 (03) ◽  
pp. 361-374 ◽  
Author(s):  
JUAN ANDRADE-CETTO ◽  
ALBERTO SANFELIU
Keyword(s):  
Learning Rule ◽  
Dynamic Environments ◽  
Position Estimation ◽  
Indoor Environments ◽  
Map Building ◽  
Robust Learning ◽  
Map Construction ◽  
Map Updating ◽  
Dynamic Map ◽  
Robot Position

A system that builds and maintains a dynamic map for a mobile robot is presented. A learning rule associated to each observed landmark is used to compute its robustness. The position of the robot during map construction is estimated by combining sensor readings, motion commands, and the current map state by means of an Extended Kalman Filter. The combination of landmark strength validation and Kalman filtering for map updating and robot position estimation allows for robust learning of moderately dynamic indoor environments.

FINITE IMPULSE RESPONSE DOUBLE DENSITY FILTER BANKS AND FRAMELETS

2013 ◽  
Vol 11 (01) ◽  
pp. 1350010
Author(s):  
ASHOKA JAYAWARDENA ◽  
PAUL KWAN
Keyword(s):  
Wavelet Transform ◽  
Impulse Response ◽  
Filter Bank ◽  
Filter Banks ◽  
Finite Impulse Response ◽  
Wavelet Filters ◽  
Density Filter ◽  
Shift Invariance ◽  
Factorization Methods ◽  
Invariant Properties

In this paper, we focus on the design of oversampled filter banks and the resulting framelets. The framelets obtained exhibit improved shift invariant properties over decimated wavelet transform. Shift invariance has applications in many areas, particularly denoising, coding and compression. Our contribution here is on filter bank completion. In addition, we propose novel factorization methods to design wavelet filters from given scaling filters.

A Finite-Impulse-Response-Based Approach to Control Acoustic-Caused Probe-Vibration in Atomic Force Microscope Imaging

2017 ◽  
Author(s):  
Sicheng Yi ◽  
Qingze Zou
Keyword(s):  
Atomic Force Microscope ◽  
Impulse Response ◽  
Controller Design ◽  
Finite Impulse Response ◽  
Feedforward Control ◽  
Acoustic Noise ◽  
Noise Cancellation ◽  
Control Approach ◽  
Atomic Force ◽  
Afm Imaging

In this paper, we propose a finite-impulse-response (FIR)-based feedforward control approach to mitigate the acoustic-caused probe vibration during atomic force microscope (AFM) imaging. Compensation for the extraneous probe vibration is needed to avoid the adverse effects of environmental disturbances such as acoustic noise on AFM imaging, nanomechanical characterization, and nanomanipulation. Particularly, residual noise still exists even though conventional passive noise cancellation apparatus has been employed. The proposed technique exploits a data-driven approach to capture both the noise propagation dynamics and the noise cancellation dynamics in the controller design, and is illustrated through the experimental implementation in AFM imaging application.

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