| Under the background of the rapid development of technological intelligence and information intelligence,the development of robot technology has advanced by leaps and bounds,and it has become a mature research field.When a single-robot system is in a complex environment or faced with heavy tasks,it is difficult to complete the corresponding work due to the limitation of its ability.Under this premise,the multi-robot system came into being.Path planning and formation control are the basis of multi-robot system work,which can ensure that the system can smoothly reach the target point according to the formation strategy while avoiding the influence of obstacles in the environment,and complete the set tasks.However,the existing algorithms have problems such as low computational efficiency and low formation flexibility.This topic takes this as the starting point to study the path planning algorithm and formation control algorithm of the robot system.The main contents are as follows:Firstly,through the research and analysis of robot path planning and multi-robot formation control,the widely used path planning algorithm and formation control algorithm are introduced,and the realization principles of various algorithms are analyzed in detail by means of formula deduction and structure diagram.Through the comparison of the advantages and disadvantages of the algorithms,the RRT algorithm and the LeaderFollower algorithm with the most improved advantages are drawn out.At the same time,under the premise of theoretical support,the performance indicators of path planning and formation control algorithms were systematically studied.The analysis and application of algorithm performance indicators also laid the foundation for the proposal of IMRRT algorithm and path planning and formation control algorithm for multi-robots.Then,aiming at the problems of strong randomness and low search efficiency in the RRT algorithm,a performance-optimized IMRRT algorithm is proposed.Based on the basic RRT algorithm,the idea of target bias is introduced,and the target orientation of new node generation is enhanced through the target node expansion weight,so that the expansion of the random tree is purposefully oriented towards the target node.In the process of expansion,the random tree adjusts the obstacle avoidance of the planned path according to the space environment,guarantees various parameter indicators while reaching the target node,and improves the problems existing in the RRT algorithm.The results of experimental simulation show that compared with the basic RRT algorithm,the RRT* algorithm,and the Informed-RRT* algorithm,the running time of the IMRRT algorithm is reduced by an average of 25.99%,56.91%,and 53.31%;And the path planning length is also reduced by an average of 7.37%,0.89%,and 0.13%.The IMRRT algorithm improves search efficiency and realizes the optimization of the planned path.Finally,a Leader-Follow control model is established,and a dynamic pilot-based multi-robot path planning and formation control algorithm is proposed.Based on the Leader-Follower algorithm model,the idea of dynamic leader is introduced to make the multi-robot formation flexible,and realize the dynamic adjustment of the pilot robot while changing the multi-robot formation.At the same time,combined with the particle model and difference model transformation method,the flexible adjustment of the path and position of multi-robots during formation transformation is realized.The cross-mode experimental simulation shows that compared with the Leader-Follower algorithm,the formation adjustment rate of multi-robot is increased by an average of 66.7% and the dynamic navigation rate of pilot robot is increased by an average of 53.35% under the action of path planning and formation algorithm for multi-robots.The algorithm not only realizes the formation adjustment of multi-robot but also effectively improves the flexibility of multi-robot formation. |
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