Path Planning And Trajectory Tracking Control For A Wheeled Mobile Robot

As a comprehensive system that integrates multiple functions such as environmental awareness,dynamic planning,and behavior control,the mobile robot has been widely used in many fields,such as industry,space,military,and civil.Mobile robots often implement some specified tasks in unknown or complex environments.Path planning and trajectory tracking control are basic and important issues for mobile robots that perform these complex tasks.Besides,due to the wide application of network communication technology,more and more control systems use the network to transmit data and signals.If the data and signals of the control system are periodically transmitted through the network,it will cause a waste of communication resources and increase the burden of the network.Thus,it is essential to find the trade-off between the network resources and the control performance.To solve such a problem,this thesis mainly studies the path planning problem of a wheeled mobile robot and its trajectory tracking control problem in the network environment.This thesis considers a continuous alternate wheeled mobile robot,and establishes its kinematics model and dynamic model.Then,a path planning algorithm for the mobile robot is designed by using ant colony algorithm.In order to avoid the shortcomings of the traditional ant colony algorithm,this thesis modifies the heuristic information function and pheromone update rules of the ant colony algorithm.By combining the second optimization on the optimal path obtained in each iteration,the proposed algorithm has higher search efficiency,faster convergence speed,and the avoidance of the local optimal as far as possible.Subsequently,this thesis presents the event-triggered control scheme for a constrained mobile robot in the network environment for two cases,where the mobile robot's model is known and partially unknown.In this thesis,the system transformation technology is employed to convert the model of the constrained mobile robot,and then a novel event-triggered condition is constructed for the transformed model,thereby effectively reducing the communication resources.Moreover,the disturbance observer and neural network approximator are designed to ease the effect of unknown disturbances and unknown dynamics on the control performance.By using the B-spline curve to smooth the above planned path,the proposed control scheme can not only guarantee that the mobile robot accurately tracks to the smooth path,but also ensure that the mobile robot satisfies the specified position constraints.Finally,the simulation experiments are operated by MATLAB to verify the effectiveness and feasibility of the proposed path planning algorithm and the trajectory tracking control scheme.