| In recent years,as the most promising technology,robots have become more and more widely used in agriculture industry,service industry and industry.With the increasing demand for robot stability,accuracy and rapidity,single robot technology can no longer meet the needs of complex work.Therefore,researchers are increasingly in-depth research on multi-robot systems.In multi-robot system,how to assign each task point to each robot according to the reasonable allocation strategy in the environment of multi-robot and multi-task point,so that it can accomplish the task optimally according to the shortest path planned,and become a research hotspot.Therefore,the study of robot task assignment and path planning is of great significance to people’s work.In order to solve the problem of multi-robot task assignment in an obstacle environment,we need to obtain the path information of the robot to each task point.In order to find A safe and non-collision feasible path from the beginning to the end,and to solve the problems existing in the path,such as under optimal local path,slow convergence speed,and many folding points,this paper proposes A global programming method based on the combination of Beetle Antennae search algorithm and A* algorithm.Firstly,A raster method is used to establish the robot workspace model.Based on A* algorithm,Manhattan distance is used as the heuristic function to obtain the original path.Secondly,path optimization is carried out by incorporating the Beetle Antennae search algorithm.Finally,Bezier curves are used for smooth processing to make the robot work smoothly.The simulation results show that compared with the smooth A* and potential field ant colony algorithm,the proposed algorithm significantly reduces the path length and the number of turning angles.In order to eliminate the randomness and chance of the algorithm,50 experiments are carried out to verify the accuracy of the results.The results provide more path information for multi-robot task assignment.After obtaining accurate path information,a task assignment algorithm based on resource auction is proposed to solve the problem of multi-robot cooperative operation in farmland environment,which is used to efficiently perform multiple tasks in the long-term task of repopulating station with robot resources.Firstly,the multi-robot task is modeled according to the problem of multi-robot task assignment,and the task energy index is analyzed.Secondly,in the task assignment,on the basisof considering the constraints of the number,working time and distance of robots,the task execution capability was added,and the resource consumption of robots during long-term task execution was considered to reduce the execution cost of the whole system and improve the task completion quantity.Through Matlab platform simulation experiment,compare and generate multi-robot and multi-task point allocation optimization results.The simulation results show that the resource-based auction algorithm can effectively improve operational efficiency and optimize resource consumption and task completion under the same conditions,which proves the effectiveness of the algorithm in this paper.Meanwhile,the calculated results in this paper are closer to the actual task completion amount,which improves the accuracy of the results.Under the development environment of Pycharm,Pyqt5 is used to complete the robot software design,and remote control is used to obtain the robot’s work data in the field through the software interface,so as to improve the planting efficiency and carry out agricultural planting more scientifically and intelligently. |
