Obstacles Avoidance And Trajectory Planning Of Mobile Robots

As core algorithm of mobile robots,navigation planning provides robots with the capability of perception and mobile work which is a hot issue in academia and industry.Robot navigation planning is generally divided into four parts with the construction of maps,self-localization,path planning and trajectory planning.In this thesis,we focus on the path planning and trajectory planning.The main research contents include the following parts:1.An improved global path planning algorithm based on generalized voronoi diagram and hybrid A*algorithm is implemented.Compared with the traditional global path planning algorithm,the method takes into account the minimum turning radius which is geometric constraint of the robots,and introduces the Reeds-Shepp optimal trajectory which skips a large number of open research spaces to improve the algorithm speed.Finally,we use gradient descent optimization to make the final path more smooth and reasonable.2.An improved trajectory planning method Timed Elastic Band based on graph optimization is proposed.In this thesis,the global path obtained by the hybrid A*algorithm is optimized as the initial value of the TEB algorithm.The trajectory tracking algorithm is used to track the trajectory of the TEB and replace the original velocity of the TEB algorithm.The joint constraint of velocity and angular velocity is further increased on the basis of the original algorithm,which makes the whole algorithm more reasonable.3.A path tracking method based on PD controller and Nonlinear Model Predictive Control(NMPC)is proposed.The trajectory tracking method based on NMPC takes into account the model information of the robot itself and improves the accuracy of trajectory tracking.The control period of trajectory planning can be kept within 40ms at all times.