AN FLC-PSO ALGORITHM-CONTROLLED MOBILE ROBOT

The ineffectiveness of the wall-following robot (WFR) performance indicated by its surging movement has been a concerning issue. The use of a Fuzzy Logic Controller (FLC) has been considered to be an option to mitigate this problem. However, the determination of the membership function of the input value precisely adds to this problem. For this reason, a particular manner is recommended to improve the performance of FLC. This paper describes an optimization method, Particle Swarm Optimization (PSO), used to automatically determinate and arrange the FLC’s input membership function. The proposed method is simulated and validated by using MATLAB. The results are compared in terms of accumulative error. According to all the comparative results, the stability and effectiveness of the proposed method have been significantly satisfied

ENHANCING THE PERFORMANCE OF THE WALL-FOLLOWING ROBOT BASED ON FLC-GA

Determination of the improper speed of the wall-following robot will produce a wavy motion. This common problem can be solved by adding a Fuzzy Logic Controller (FLC) to the system. The usage of FLC is very influential on the performance of the wall-following robot. Accuracy in the determination of speed is largely based on the setting of the membership function that becomes the value of its input. So manual setting on membership function can still be enhanced by approaching the certain optimization method. This paper describes an optimization method based on Genetic Algorithm (GA). It is used to improving the ability of FLC to control the wall-following robot controlled by FLC. To provide clarity, the wall-following robot that controlled using an FLC with manual settings will be simulated and compared with the performance of wall-following robots controlled by a fuzzy logic controller optimized by a Genetic Algorithm (FLC-GA). According to comparative results, the proposed method has been showing effectiveness in terms of stability indicated by a small error

Improving a Wall-Following Robot Performance with a PID-Genetic Algorithm Controller

A wall-following robot needs a robust controller that navigate robot based on the specified distance from the wall. The usage of PID controller has been successfully minimizing the dynamic error of wall-following robot. However, a manual setting of three unknown parameters of PID-controller often precisely increase instability. Hence, recently there are many approaches to solve this issue. This paper presents an approach to obtaining those PID parameters automatically by utilizing the role of Genetic Algorithm. The proposed method was simulated using MATLAB and tested in a real robot. Based on several experiments results it has been showing the effectiveness of reducing the dynamic error of the wall-following robot

A MAPAEKF-SLAM ALGORITHM WITH RECURSIVE MEAN AND COVARIANCE OF PROCESS AND MEASUREMENT NOISE STATISTIC

The most popular filtering method used for solving a Simultaneous Localization and Mapping is the Extended Kalman Filter. Essentially, it requires prior stochastic knowledge both the process and measurement noise statistic. In order to avoid this requirement, these noise statistics have been defined at the beginning and kept to be fixed for the whole process. Indeed, it will satisfy the desired robustness in the case of simulation. Oppositely, due to the continuous uncertainty affected by the dynamic system under time integration, this manner is strongly not recommended. The reason is, improperly defined noise will not only degrade the filter performance but also might lead the filter to divergence condition. For this reason, there has been a strong manner well-termed as an adaptive-based strategy that commonly used to equip the classical filter for having an ability to approximate the noise statistic. Of course, by knowing the closely responsive noise statistic, the robustness and accuracy of an EKF can increase. However, most of the existed Adaptive-EKF only considered that the process and measurement noise statistic are characteristically zero-mean and responsive covariances. Accordingly, the robustness of EKF can still be enhanced. This paper presents a proposed method named as a MAPAEKF-SLAM algorithm used for solving the SLAM problem of a mobile robot, Turtlebot2. Sequentially, a classical EKF was estimated using Maximum a Posteriori. However, due to the existence of unobserved value, EKF was also smoothed one time based on the fixed-interval smoothing method. This smoothing step aims to keep-up the derivation process under MAP creation. Realistically, this proposed method was simulated and compared to the conventional one. Finally, it has been showing better accuracy in terms of Root Mean Square Error (RMSE) of both Estimated Map Coordinate (EMC) and Estimated Path Coordinate (EPC).     

THE ACA-BASED PID CONTROLLER FOR ENHANCING A WHEELED-MOBILE ROBOT

Wall-following control of mobile robot is an important topic in the mobile robot researches. The wall-following control problem is characterized by moving the robot along the wall in a desired direction while maintaining a constants distance to the wall. The existing control algorithms become complicated in implementation and not efficient enough. Ant colony algorithm (ACA), in terms of optimizing parameters, has a faster convergence speed and features that are easy to integrate with other methods. This paper adopts ant colony algorithm to optimize PID controller, and then selects ideal control parameters. The simulation results based on MATLAB show that the control system optimized by ant colony algorithm has higher efficiency than the traditional control systems in term of RMSE

Maximum likelihood estimation-assisted ASVSF through state covariance-based 2D SLAM algorithm

The smooth variable structure filter (ASVSF) has been relatively considered as a new robust predictor-corrector method for estimating the state. In order to effectively utilize it, an SVSF requires the accurate system model, and exact prior knowledge includes both the process and measurement noise statistic. Unfortunately, the system model is always inaccurate because of some considerations avoided at the beginning. Moreover, the small addictive noises are partially known or even unknown. Of course, this limitation can degrade the performance of SVSF or also lead to divergence condition. For this reason, it is proposed through this paper an adaptive smooth variable structure filter (ASVSF) by conditioning the probability density function of a measurementto the unknown parameters at one iteration. This proposed method is assumed to accomplish the localization and direct point-based observation task of a wheeled mobile robot, TurtleBot2. Finally, by realistically simulating it and comparing to a conventional method, the proposed method has been showing a better accuracy and stability in term of root mean square error (RMSE) of the estimated map coordinate (EMC) and estimated path coordinate (EPC)

A compliant-mechanism-based lockable prismatic joint for high-load morphing structures

Lockable joints are widely used in robotic systems and adaptive structures for energy management and/or topology reconfiguration. However, it is still challenging to design a joint with desired properties, including high locking load, infinite locking positions, short switching time, energy-efficient control, and a compact and lightweight structure. This paper aims at this open problem by presenting a novel piezoelectric (PZT) actuated lockable prismatic joint. This joint is a compliant mechanism (CM) consisting of a compound bridge-type compliant mechanism (CBCM) and a pair of compound multibeam parallelogram mechanisms (CMPMs). It can produce the required input/output stiffness to transmit large forces for high-load locking. It can also provide a desired input/output motion range for PZT actuation-based unlocking and for facilitating preloading adjustment. An analytical model is presented based on a compliance matrix method and the nonlinear model of the CMPM to predict the joint's static characteristics under various input/output conditions. A two-step optimization framework is proposed for locking applications. The theoretical study and nonlinear FEA/experimental verification confirm the feasibility of the design and the accuracy of the proposed model

Multifocus Image Fusion in Q-Shift DTCWT Domain Using Various Fusion Rules

Multifocus image fusion is a process that integrates partially focused image sequence into a fused image which is focused everywhere, with multiple methods proposed in the past decades. The Dual Tree Complex Wavelet Transform (DTCWT) is one of the most precise ones eliminating two main defects caused by the Discrete Wavelet Transform (DWT). Q-shift DTCWT was proposed afterwards to simplify the construction of filters in DTCWT, producing better fusion effects. A different image fusion strategy based on Q-shift DTCWT is presented in this work. According to the strategy, firstly, each image is decomposed into low and high frequency coefficients, which are, respectively, fused by using different rules, and then various fusion rules are innovatively combined in Q-shift DTCWT, such as the Neighborhood Variant Maximum Selectivity (NVMS) and the Sum Modified Laplacian (SML). Finally, the fused coefficients could be well extracted from the source images and reconstructed to produce one fully focused image. This strategy is verified visually and quantitatively with several existing fusion methods based on a plenty of experiments and yields good results both on standard images and on microscopic images. Hence, we can draw the conclusion that the rule of NVMS is better than others after Q-shift DTCWT

Inhomogeneous microstructure and fatigue crack propagation of thick-section high strength steel joint welded using double-sided hybrid fiber laser-arc welding

The inhomogeneous microstructure and fatigue crack propagation of 30 mm thick-section high strength steel welded joint by double-sided hybrid fiber laser-arc welding were investigated in detail. The results indicated that the average effective grain size of the laser zone was only 1/2 of that of the arc zone, due to the faster cooling rate of the laser resource. The base metal consisted of massive polygonal ferrites and small granular carbides, while fine grained region, the coarse grained region and weld metal were all composed of martensite with a high dislocation density. Compared with the arc zone, the percentage of grain boundaries with high misorientation angle increased 24% for the laser zone, as the average grain size of the laser zone was smaller than that of the arc zone. The results also revealed that the fatigue crack propagation resistance of the welded joint was higher than that of the base metal. Meanwhile, a significant increase in the fatigue crack propagation resistance of the laser zone occurred, as compared with the arc zone, due to the refined grains and the high proportion of the grain boundaries with high misorientation angle (>15°) in the laser zone

Atomic Layer Deposition of Buffer Layers for the Growth of Vertically Aligned Carbon Nanotube Arrays

Vertically aligned carbon nanotube arrays (VACNTs) show a great potential for various applications, such as thermal interface materials (TIMs). Besides the thermally oxidized SiO 2 , atomic layer deposition (ALD) was also used to synthesize oxide buffer layers before the deposition of the catalyst, such as Al 2 O 3 , TiO 2 , and ZnO. The growth of VACNTs was found to be largely dependent on different oxide buffer layers, which generally prevented the diffusion of the catalyst into the substrate. Among them, the thickest and densest VACNTs could be achieved on Al 2 O 3 , and carbon nanotubes were mostly triple-walled. Besides, the deposition temperature was critical to the growth of VACNTs on Al 2 O 3 , and their growth rate obviously reduced above 650 \ub0C, which might be related to the Ostwald ripening of the catalyst nanoparticles or subsurface diffusion of the catalyst. Furthermore, the VACNTs/graphene composite film was prepared as the thermal interface material. The VACNTs and graphene were proved to be the effective vertical and transverse heat transfer pathways in it, respectively