Research On Path Tracking And Arm Motion Planning For Mobile Robots

With the advent of information technology and intelligence,scientists have continuously improved the performance requirements of mobile robots.It represents the latest research in the fields of automatic control,computer,artificial intelligence and the highest achievements of mechatronics.Compared with traditional industrial robots,mobile robots with autonomous sensing,decision-making and execution functions have broad application prospects.In the fields of national defense,industrial and agricultural production,emergency rescue,highly repetitive operations and indoor services,there are enormous advantages that human beings cannot match.This paper takes the mobile robot with the robot arm as the research object,and focuses on the path planning and tracking of the mobile robot and the motion planning of the robot arm after reaching the destination.The following research is done:An overview of the development of robots and the current state of application of mobile robots without arms and arms.Explain the image processing method,that is,how to convert the color image obtained by monocular vision into a binary image.Then,based on the image processing,the target object is identified and located,and the distance between the robot and the target object is measured,and the coordinates of the target object in the world coordinate system are obtained.An ant colony path planning algorithm guided by potential field forces is proposed.The algorithm transforms the force factor in the artificial potential field method into a pheromone weight in an ant colony algorithm,which can accelerate the convergence speed of the ant colony algorithm at the beginning.And with the increase of the number of iterations,the influence of force factors on ants is gradually reduced.When falling into local optimum,the possibility of ant colony algorithm falling into local optimum is reduced by retreating.Finally,the curve fitting of the path is implemented by the least squares method,so that the robot can perform path tracking.An algorithm combining wavelet function and predictive function control is proposed to realize the path tracking of the robot.The algorithm utilizes the compact locality and multi-scale analysis characteristics of wavelets.The number and position distribution of the basis functions can be flexibly set according to the system control precision and different approximation requirements of different prediction periods.It not only optimizes the overall error performance,but also highlights the approximation requirements of important fitting points,and achieves the assembly of optimized variables.The algorithm can better realize the robot path tracking control.After the robot moves to the target area,the arm needs to reach the target point to grab the target.In order to improve the operating efficiency of the robot arm,the running path of the robot arm is smooth and continuous,and the utility of the mechanical arm is enhanced.Under the condition of optimal time,a strategy of using particle swarm algorithm to trajectory planning of robot arm with B-spline curve is proposed,and the time interval of each spline curve is optimized.It can shorten the time interval of each curve and improve the operating efficiency of the robot arm.