In this study, a gravitational search algorithm has been proposed to design the optimal route of mobile robot in certain and known environments or relatively unknown environments (static or dynamic). Reviews in this paper, indicates proper operation of the algorithm in More
In this study, a gravitational search algorithm has been proposed to design the optimal route of mobile robot in certain and known environments or relatively unknown environments (static or dynamic). Reviews in this paper, indicates proper operation of the algorithm in terms of convenience and simplicity in running processes time consuming offline and online. Also, as well as the results of the review period and the path to achieve the optimal route in dynamic environments and static is Representative and shower the strength of the evolutionary algorithm than other evolutionary algorithms in the field. Finally, the experimental results are indicated a superior performance gravitational search algorithm than other evolutionary algorithms available (algorithms, particle swarm) which discussed in this research. This topic has had a significant impact on the design direction of the static and dynamic, especially in the environment Dynamic.
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The reference trajectory tracking is one of the most important issues in the field of tractor-trailer wheeled mobile robots control. In this paper, thetrajectory tracking control issues of a tractor-trailer wheeled mob­ile robot has been significantly solved in the More
The reference trajectory tracking is one of the most important issues in the field of tractor-trailer wheeled mobile robots control. In this paper, thetrajectory tracking control issues of a tractor-trailer wheeled mob­ile robot has been significantly solved in the presence of structural uncertainties,non-hol­o­­n­o­mic constraints and external disturbance. The proposed scheme is based on a design that the tractor-trailer’s state space representation is extracted from its dynamic and ki­n­­e­matic models and presented ina companion format first. In the following,by considering the state space representation of system, the control algorithm is presented includingtwo external and internal control loops. Toward this end, the control law has been developed in the inner loop via input-output feedback linearization in a nonlinear feedback formwh­i­­ch is continuously eliminating the nonlinear dynamics of the system. Then,by using a comb­ination of the output that is pr­o­duced in linearization steps with a terminal sliding mode control algorithm and sketching a neural robust ad­aptive finite time controller in the outer loop, the accurate and fast performance of the closed loop system has been guar­a­nteed in the presence of uncertainties. The proposed control algorithmfinally guarantees the boundedness of closed-loop signals and accurate finite time convergence of tracking errors. At the end, the effectiveness of the proposed sch­eme has been demo­nstrated and shown through the extended Lyapunov theorem and simulated by MATLAB application.
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Path planning of mobile robots is one of the important issues in the field of robotics. Also, optimizing the path length and crossing the local minima traps are the basic and up-to-date challenges in this field. One of the important methods in path planning of these rob More
Path planning of mobile robots is one of the important issues in the field of robotics. Also, optimizing the path length and crossing the local minima traps are the basic and up-to-date challenges in this field. One of the important methods in path planning of these robots is the artificial potential field method. Because it is based on simple mathematical calculations. One of the most important disadvantages of this method is getting trapped in local minima situations. One approach for solving the problem of local minima is to use optimization methods to find suitable coefficients (attractive and repulsive) and step length that can solve local minima and optimize the path length. The Harris Hawks algorithm is a powerful and new meta-heuristic algorithm in the field of optimization that is based on population and inspired by the life of Harris Hawks in nature. This algorithm has been able to prove its superiority over similar optimization methods in finding the optimal solution, faster convergence, lower computational time and not trapping in local minima. This method has not been used in the path planning of mobile robots. In order to eliminate the disadvantages of the artificial potential field method and to optimize the path length, the Harris Hawks algorithm has been used in this paper. The simulation results showed that the combination of the artificial potential field method and the Harris Hawks algorithm can solve the local minima problem and optimize the path length, increase the path efficiency and reduce the convergence time.
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In this paper, we investigate a hybrid controller for wheeled mobile robots in the presence of external disturbances and parametric uncertainty. Robot models include kinematic and dynamic equations of motion. In this paper, in order to reach the final position, the whee More
In this paper, we investigate a hybrid controller for wheeled mobile robots in the presence of external disturbances and parametric uncertainty. Robot models include kinematic and dynamic equations of motion. In this paper, in order to reach the final position, the wheeled moving robot must be controlled in such a way that it can follow a reference path. Many studies often use a motion control strategy for the wheeled mobile robot. In this study, the proposed control strategy has two stages including cinematic control and dynamic control. In this regard, first after introducing the kinematic model of the robot, we design a predictive controller for this part and prove it. Then, based on the nonlinear dynamic dynamics of the robot, an adaptive sliding mode dynamic controller is introduced to estimate the disturbances online, automatically adjust the gain of the control and eliminate the umbrella phenomenon completely. Then, the proposed design is analyzed and proved using Lyapanov's theory of stability. According to the proposed adaptive control law, optimal convergence and tracking performance of all signals are guaranteed and tracking errors can converge arbitrarily in finite time to the source. Simulation results have been performed to show the effectiveness of the proposed design using Matlab software.
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Numerous methods have been developed to solve the path planning problem, among which the visibility graph, Voronoi diagram, Quad-Tree and Wave-Front are well-known techniques. In this paper, a new global path planning algorithm named HYBRID-Visibility-QuadTree-Voronoi-W More
Numerous methods have been developed to solve the path planning problem, among which the visibility graph, Voronoi diagram, Quad-Tree and Wave-Front are well-known techniques. In this paper, a new global path planning algorithm named HYBRID-Visibility-QuadTree-Voronoi-WaveFront method (HYBRID-VQVW) is presented where these four methods are integrated in a single architecture. After constructing these global trajectories of C-space, the best trajectory among four is selected in every sampling distance by several criterions. These criterions consist of length, smoothness and safety of the trajectory. In fact, the algorithm provides a parametric tradeoff between shortest, safest and smoothest paths and generally yields shorter and smoother paths than the Voronoi, Quad-Tree and Wave-Front methods, and safer than the visibility graph.
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This paper introduces and discusses a new control strategy for nonholonomic wheeled mobile robots (WMR). Robot models include kinematic and dynamic equations of motion. A barrier function adaptive terminal sliding mode control is used to control the movement of the robo More
This paper introduces and discusses a new control strategy for nonholonomic wheeled mobile robots (WMR). Robot models include kinematic and dynamic equations of motion. A barrier function adaptive terminal sliding mode control is used to control the movement of the robot. It considers sliding mode control (SMC) to deal with the dynamic model uncertainties of the chaos system, and uses a combination of SMC with an adaptive control approach to solve the upper boundaries problem of unknown model uncertainties and their estimation. Chattering is completely eliminated without over estimating the control gains by adopting an adaptive continuous barrier function in the dynamic switching function. Using the Lyapunov's stability theory, it was shown that the proposed scheme can guarantee the convergence of system states to the vicinity of the sliding surface in finite time. Additionally, the adoption of a sliding surface with a nonlinear and integral switching function resulted in removing the reaching phase of the sliding surface and yielding a controller that is robust to uncertainties from the start. The effectiveness of the proposed control method was assessed using three scenarios implemented to a Liu's uncertain chaotic system in MATLAB/Simulink environment. The obtained results confirmed the ability of the proposed approach to achieve continuous and smooth control rules for such chaotic systems. Among the main attributes of the proposed control method are its ability to completely eliminate chattering and yield a robust performance against model uncertainties and unknown external disturbances.
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در این تحقیق روشی برای طراحی مسیر یک سیستم ربات پایه متحرک فضایی شامل پایه غیرهلونومیک و بازوی سه عضوی در حضور موانع ثابت و متحرک ارائه شده است. در اینجا از توابع پیوسته و هموار مانند توابع چندجملهای به منظور مسیریابی ربات استفاده شده است. روش ارائه شده شامل به دست آور More
در این تحقیق روشی برای طراحی مسیر یک سیستم ربات پایه متحرک فضایی شامل پایه غیرهلونومیک و بازوی سه عضوی در حضور موانع ثابت و متحرک ارائه شده است. در اینجا از توابع پیوسته و هموار مانند توابع چندجملهای به منظور مسیریابی ربات استفاده شده است. روش ارائه شده شامل به دست آوردن تاریخچه زمانی حرکت محرکهای ربات میشود که تحت رفتار این محرکها، ربات به پیکربندی نهایی خود میرسد. پایه بهکار رفته در این تحقیق، پایه با رانش دیفرانسیلی است که از انواع پرکاربرد پایههاست. بازوی مکانیکی واقع بر پایه نیز بازوی سه درجه آزادی فضایی است. ترکیب بازو و پایه باعث میشود که ربات در فضای کاری وسیع تری عمل کند. هر چند بررسی این نوع سیستمها شامل بررسی مسئله به نام افزونگی درجات آزادی میشود که به پیچیدگی مسئله میافزاید، ولی افزونگی درجات آزادی در ربات، قابلیتهای ویژهای از نظر کاربردی برای آنها ایجاد میکند. در رباتهای دارای افزونگی درجات آزادی در یک فضای کاری مشخص، مسیرهای متعددی برای ربات وجود دارد. یک راه برای انتخاب یک مسیر مناسب از بین مسیرهای ممکن، انتخاب یک اندیس مناسب و بهینه کردن آن است. نتایج عددی و نمودارها جهت طراحی مسیر بهینه برای یک مجموعه ربات پایه متحرک در حضور موانع با استفاده از روش الگوریتم ژنتیک آورده شده است. موانع بهکار رفته در مسئله نیز فضایی بوده و موانع ثابت و متحرک را شامل میشود.
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