Research On Path Planning Of Warehouse Mobile Robot Based On Improved Harris Hawks Algorithm And Dynamic Window Approach

As one of the key technologies of mobile robot autonomous navigation,path planning is of great significance in improving storage and transportation efficiency and reducing labor cost,and has gradually become a hot topic in mobile robot research.However,in practical application,due to the complex and changeable real scene,mobile robots still have problems such as low efficiency and poor adaptability in the process of transporting goods to the selection area.To solve the above problems,this paper combined global path planning and local path planning to study the problem of mobile robot path planning,and proposed a fusion algorithm based on improved Harris Hawks optimization algorithm and Dynamic Window Approach to improve the effect of robot path planning.The details of the paper are as follows:(1)To overcome the shortcomings of low search efficiency and easy to fall into the local optimal,we propose an improved Harris Hawks algorithm with the integration of multistrategies.Tent chaotic mapping was used to initialize the population to increase the diversity of the population.The exponential function was integrated into the prey control mechanism to achieve an effective balance between global optimization and local optimization.The Cauchy reverse learning variant strategy is used for perturbation to avoid the algorithm falling into local optimality.The comparison experiment shows that the improved Harris Hawks algorithm can reduce the optimal path length and improve the algorithm performance.(2)Aiming at the defects of traditional Dynamic Window Approach in path planning problem,such as unreachable target and falling into local optimum,this paper proposed to improve the problem by using obstacle expansion model and target distance evaluation subfunction.By analyzing the kinematic model and mechanical structure of the mobile robot,the obstacles are expanded to improve the safety of the path.Meanwhile,the target distance evaluation subfunction is used to improve the flexibility and stability of the robot during operation.The algorithm is shown to have good dynamic obstacle avoidance performance in the simulation experiments.(3)Aiming at the problems that mobile robots cannot autonomously avoid dynamic obstacles in the global area and are prone to the unreachable target points in the local area,the improved Harris Hawks algorithm is integrated with the Dynamic Window Approach.The inflection point of the optimal path generated by the improved Harris Hawks algorithm at the global level is taken as the local target point,and the local path planning is carried out in real time,so that the mobile robot can dynamically avoid obstacles when moving along the global optimal path.In order to verify the effectiveness and applicability of the fusion algorithm,the path planning performance of the mobile robot in static and dynamic environment was verified respectively in the MATLAB simulation experiment platform and the mobile intelligent vehicle experiment platform in the actual scene.