Research And Application Of Robot Path Planning Algorithm

Various types of mobile robots have already entered people's field of vision,and more and more experts and scholars have joined the ranks of research robots,and planning a safe and effective travel path based on pathfinding algorithms has become a key technology for mobile robots.Therefore,the analysis of path planning algorithms has particularly important theoretical and practical significance.This article chooses the currently popular global path planning A* search algorithm,and also chooses the local artificial potential field method and fuzzy logic path finding algorithm for research,analysis and discussion.The traditional A* algorithm can quickly bypass obstacles and find the final target point smoothly.But the disadvantage of the traditional A* algorithm is that the planned path it generates is not smooth enough and there are many turning points.The traditional A*algorithm is optimized,the process of converting polyline path nodes into arc path nodes is added,and the minimum safety distance is set.The traditional A* algorithm and the improved A* algorithm were simulated.It was found that the improved A* algorithm slightly increased the optimal path search time because of the addition of arc path processing steps,but the planned path distance It is shorter and the route is smoother,avoiding the corner points of obstacles,and solving the shortcomings of the traditional A*algorithm.The traditional artificial potential field method is relatively smooth,but it also has disadvantages.The first is because the obstacle and the target point are too close,the repulsive force will be greater than the gravitational force of the target point,there is a problem that the target point is unreachable.The second is that when the position is at the equilibrium point where the repulsive force and the resultant force cancel each other out,it will stop pathfinding and fall into a local minimum.For the problem of unreachable target,the expression formula of obstacle repulsion can be changed to reduce the obstacle repulsion near the target point.When the robot reaches the local minimum point,it reaches the dynamic balance of the force.At this time,additional force can be added to break thisbalance,so that the robot leaves the local minimum point,and the additional force is cancelled after leaving.The simulation experiment shows that the above two problems in this paragraph are solved well.The fuzzy logic algorithm can plan a path to the target point even in the face of complex scenes,but the generated path is not smooth enough,and it does not take into account the physical volume of the mobile robot,which is likely to collide with obstacles during the pathfinding process Security,if you want to ensure security,you need to add a lot of fuzzy rules to deal with the complex and changeable environment.When using fuzzy logic algorithms for path planning,if you want to get the overall optimal result,you must add more detailed fuzzy rules.As the fuzzy rules increase,storage space will increase,and the calculation time of path planning will be longer.With the help of the combined algorithm of fuzzy logic and artificial potential field method,the effect of complementing each other can be achieved.The path point calculated by the fuzzy logic algorithm planning is used as the sub-target point of pathfinding.Using the artificial potential field method to plan the path of the sub-target points,a relatively smooth path can be obtained,and finally the target point is gradually reached.This path-finding combination algorithm can also be applied to more complex scenes.The above three traditional algorithms are simulated on MATLAB,the experimental results are analyzed and discussed,the advantages and disadvantages of traditional path finding algorithms are summarized,and the shortcomings are improved and simulated experiments are carried out.Through multiple sets of comparative simulation tests,the feasibility and safety of the improved algorithm are verified...