| In the practical application,due to the variability of working conditions and the difference of the task complexity,there are many situations where a single robot can't complete the task,especially in environment that the dynamic task is complicated and the situation is special.It is necessary to use multiple robots or mix robots of different types to work together.In this paper,the path planning problem of heterogeneous aerial-ground robot system composed of ground mobile robot and aerial flying robot is studied.The main work is as follows:First of all,this paper introduces the background and significance of the research of heterogeneous robot system,summarizes the research status of robot path planning,and puts forward the research content of this paper.Secondly,this paper briefly introduces the theory of mixed integer programming,and expounds the principle of establishing the objective function and constraint expression in different programming models,then taking the mobile robot which is an isomorphic single robot as an example,the application of convex optimization model in path planning is analyzed.Then,research on the optimal path planning problem of heterogeneous robot system accessing sub task points,to ensure that the heterogeneous robot system to make full use of their respective characteristics to achieve complementary advantages,by satisfying the neighborhood constraints of the sub task points and the obstacle avoidance constraints of the ground mobile robot,using mathematical optimization modeling method,a globally optimal or approximate optimal safe collision free path is obtained under the condition that the moving target is reachable,and the path is smoothed.Finally,the simulation is verified in MATLAB.The planning results is comparatively analyzed in several different conditions,which respectively are in the several different conditions,in the general environment,after adding the neighborhoodconstraints,adding a penalty term and considering the autonomous obstacle avoidance of ground mobile robot.The feasible and effective of the proposed algorithm is proved by the simulation results. |