Path Planning Of Indoor Service Robot Based On Firework Potential Field Method

In recent years,indoor service robots have developed rapidly,and the level of intelligence of robots has also been continuously improved.Path planning is an indispensable link in the field of mobile robots,and it is also a research hotspot in the field of intelligent robots.At present,there is a search for path planning of indoor service robots.Long time,low search path efficiency,and many path nodes generated make the robot deflect more times.Therefore,this paper combines the firework algorithm with the artificial potential field method to optimize and improve such problems.The main work is as follows:(1)Aiming at the optimal problem of the traditional firework algorithm,which has large randomness and easy to fall into a small range,an improved firework algorithm is proposed.The algorithm uses the position information of the current path node and the previous path point as the applicability function,and introduces a penalty.The function filters out the sparks falling in the obstacle area,thereby reducing the path cost;introduces a non-zero factor ? to solve the local optimization problem caused by the firework algorithm's optimal smoke explosion radius of 0;the path planned for the firework algorithm may pass through the obstacle For the problem of objects,obstacle avoidance strategies are introduced to avoid routes that may cross obstacles.(2)Aiming at the problem that the artificial potential field method path planning is prone to the target position cannot be reached,this paper introduces a distance factor in the repulsion field function,so that the repulsion force is adjusted in real time with the distance information between the target position and the robot;avoiding the robot being equal to the repulsion force of the target point The repulsive force and time generated by various obstacles linger and fall into a regional trap.In the gravitational field function and the repulsive field function,respectively,the enhancement factor and the sharp reduction factor are introduced,and the path planning of the improved potential field method is carried out in a static environment to verify The effectiveness and feasibility of this improvement;when there are obstacles in motion in the environment,the relative speed information is introduced,so that the potential field method can avoid collisions with dynamic obstacles and improve the obstacle avoidance ability of the robot.(3)The improved firework algorithm and the improved artificial potential field method are combined.The improved firework algorithm is first used to plan the global optimal path.When the robot travels within the repulsion range of the dynamic obstacle,it switches to the improved potential field method for real-time obstacle avoidance.After completing the dynamic obstacle avoidance,return to the original global optimal path to complete the path planning in the entire environment.This paper verifies the feasibility of the improved algorithm through MATLAB 2019 b simulation software,and effectively reduces the total path length.(4)Based on the ROS platform,a path planning experiment was conducted using the improved algorithm in this paper.Under different obstacles,the global path planning based on IFWA and the path planning based on IFWA-APF are experimentally verified.The experimental results show the effectiveness and feasibility of the improved algorithm in this paper.