| The mobile platform has the characteristics of wide range of motion and flexible obstacle avoidance,which is convenient for motion planning of multiple scenes,and the six-axis collaborative robotic arm has the advantages of large load,wide range of joint motion,and strong human-machine interaction properties,etc.By connecting the two through linear modules,the mobile robotic arm has more significant characteristics,and has a wider range of applications in the fields of intelligent agriculture,medical assistance,intelligent services and aerospace.The mobile robotic arm has more significant characteristics and has wider applications in the fields of smart agriculture,medical assistance,intelligent services and aerospace.At present,there is less research on redundant mobile robotic arms,and some of the kinematics and obstacle avoidance path planning problems are still imperfect,which limits its wider engineering applications.In this paper,the wheeled mobile robotic arm,which is a combination of YHS-FR07 wheeled mobile platform,YBSC17 linear module,and AUBO-i10 six-axis collaborative robotic arm,is studied in terms of overall positioning construction,obstacle avoidance trajectory planning of the mobile chassis,and motion planning of the robotic arm.Specifically,it includes the following aspects:(1)Establishing the kinematic model of the mobile robotic arm,and the modeling of the ROS platform.Firstly,the kinematic modeling of the wheeled mobile platform is carried out according to its structure and driving mode;secondly,the positive kinematic model is established by the improved D-H modeling method,and the inverse kinematic model is established by the numerical solution method of the inverse Jacobi matrix;then,the coordinate system transformation is used to combine the two kinematic models together,and the mapping of the end position of the operating arm of the system in the world coordinate system is obtained Finally,in order to meet the requirements of the subsequent simulation experiments,the overall experimental prototype is modeled in the ROS platform according to the attributes and indicators of the research object.(2)Design the velocity control law of the wheeled mobile chassis motion.As the linear module and collaborative robot arm are placed on the mobile chassis,the load of the mobile chassis is very large(load 50kg),and it is very easy to cause the overall rollover or tire skid due to its acceleration or steering too fast.By setting the maximum speed,the maximum angular speed and the acceleration appropriate to the motion state,the wheeled mobile chassis motion speed control law is designed to achieve safe and efficient tracking of the target point by the mobile chassis;finally,experiments are conducted on the ROS platform,and it is verified that the speed control law can greatly improve the tracking efficiency while ensuring it is at a safe speed.(3)Global environment positioning construction and obstacle avoidance trajectory planning of the mobile chassis.In order to realize the task of mobile robotic arm in complex working environment,it is necessary to plan the obstacle avoidance trajectory of the robot chassis,and the prerequisite for trajectory planning is a map of global nature.Firstly,this paper proposes a Gmapping improvement algorithm based on particle filtering to build a map,and verifies through experiments that the optimized Gmapping algorithm can provide a more accurate map for subsequent obstacle avoidance research;secondly,this paper introduces the concept of jump point search to optimize the A*obstacle avoidance trajectory planning algorithm to reduce the cost of algorithm search nodes and improve the efficiency of algorithm search;finally,through Finally,the optimized A*algorithm is experimentally verified to improve the path planning efficiency.(4)Research on trajectory planning and obstacle avoidance of redundant robotic arm.Firstly,multiple trajectory interpolation methods for redundant robotic arm in joint space and Cartesian space are established;secondly,for the trajectory planning of redundant robotic arm for obstacle avoidance,the number of iterations of RRT*algorithm is reduced and the number of samples is compressed by introducing the idea of target gravity,so as to accelerate the convergence speed of path expansion,and the trajectory is pruned and smoothed by using the principle of triangular inequality and B-sample curve,so as to improve the mechanical arm’s obstacle avoidance trajectory planning efficiency;finally,the comparison experiment before and after the optimization of RRT*algorithm shows that the planning time of the optimized algorithm is shortened by more than 43%,which effectively improves the search efficiency of the algorithm. |
