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nonholonomic mobile robots are widely used in industrial environments due to their extended workspace. Also, to increase the productivity and efficiency of the mobile robot, their path planning is an important task, and is attracted attention of many of robotic scientists. In this paper, the optimal path planning of the wheeled mobile robots are performed considering their nonlinear dynamic equations and the nonholonomic constraints. Problem of the trajectory optimization is formulated, and conditions of the optimality are derived as a set of nonlinear differential equations by means of indirect method of optimal control method. Then, the optimality equations are solved numerically, and variant simulations are executed. To verify the simulation study, some experimental analysis are done for the Scout mobile robot and compared to the simulation results. The experimental analysis verifies the simulation results, and demonstrates the applicability of the proposed method for the optimal path planning of the mobile robots.

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This paper investigates the leader-follower formation control problem of nonholonomic mobile robots based on backstepping technique composed with the bio-inspired neurodynamics while avoiding collision with obstacles. Kinematics model of robot and nonholonomic constraint are introduced and formation control scheme is formed based on backstepping technique. In order to solve velocity jump in backstepping kinematics model, the bio-inspired neurodynamic approach is used. In most of the previous studies, researches are used separation-bearing approach and also supposed that desired separation and bearing are constant. In this paper this assumption is relaxed and desired separation and bearing are considered to be time varying. Error dynamics equations are derived and a new controller is proposed. Also an auxiliary reference angular velocity control law is proposed to guarantee global asymptotic stability of the followers and local asymptotic stability of the entire formation according to direct method of Lyapunov. A common example of changing the formation is obstacle avoidance, when an obstacle is located within a follower path and is not in its leader path. Time varying functions for desired separation and bearing are chosen and the new controller is developed with its proof of stability. Simulations results reveal that each follower robot can track its real time leader employing the proposed kinematic controller while avoiding obstacles. Furthermore control inputs at the start moment and also while avoiding obstacles, do not contain impractical jumps and are reasonable thanks to integrating bio-inspired neurodynamic with backstepping technique.

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In this article, a novel control of wheeled mobile robot based on machine vision is considered. One of the common methods for controlling such systems is the use of Model Predictive Control (MPC) algorithms. In these systems, the response speed of the control algorithm and the optimality of these are two basic factors for achieving the optimal performance. Also, the impossibility of achieving precise values of the robot parameters and their variation during the operation of the robot is an important challenge in the implementation of the controller, therefore, this paper focuses on real-time and robust MPC, so that it can ensure the system against uncertainties and environmental disturbances in addition to the optimal and real-time response. Hence, the optimization based on projection recurrent neural network (PRNN) has been used as an optimizer to reduce the calculation time cost. The combination of PRNN optimization with MPC leads to new formulation and constraints that are considered to be the article innovations. Finally, in order to verify the validity of the proposed algorithm, the robot passes through the corridor with the presence of obstacles, which is simulated in the V-REP software. The results show that the optimum control input speed has been increased in comparison with similar methods, and the optimal path selection by the fuzzy system in the presence of obstacles has been well suited.