Three-dimensional Path Planning Of Multiple Mobile Agents Based On Intelligent Optimization Algorithm

A multi-agent system formed by multiple agents through coordinated control can improve the computing power and coverage of a single agent system,and path planning technology is one of the core contents in the field of agent research,and the multi-agent system compared with the single agent system,path planning has some particularities and complexity.This thesis mainly uses the ant colony algorithm to study the cruising path planning problem,the global shortest path planning problem and the multi-agent system formation and reorganization path planning problem in the agent's global path planning problem.This thesis takes agent path planning as the research goal.Firstly,a polymorphic ant colony algorithm based on improved state transition strategy is designed to solve agent cruise path planning problems.Then an elite based on improved state transition strategy is designed Ant colony algorithm is used to solve the global shortest path planning problem for agents.Finally,an ant colony algorithm based on 2-Opt optimization is designed to solve the multi-agent system formation and reorganization path planning problem.The work innovation of this thesis is mainly reflected in the following three aspects:(1)Combining the constraints of the path planning problem with the characteristics of the ant colony algorithm,a polymorphic ant colony algorithm based on an improved state transition strategy is designed.Aiming at the defect of the search deadlock in the polymorphic ant colony algorithm,a new design Based on the state-state probability formula,the search deadlock problem is solved on the basis of retaining the advantage that the polymorphic ant colony algorithm can effectively reduce the search subspace size.The results of simulation experiments show that the algorithm has high search efficiency and convergence speed.(2)By improving the state transition probability formula and adding the elite strategy to the iterative steps of the ant colony algorithm,an elite ant colony algorithm based on the improved state transition strategy is designed.Defects,redesigned the formula of state transition probability,enhanced the purpose of algorithm search;and added an elite strategy,which can timely feedback the new optimal solution path to the pheromone update on the path,thereby avoiding falling into local Optimal solution.The results of simulation experiments show that the algorithm has better search results,and ensures the convergence speed of the algorithm,and has strong robustness in the search results.(3)By studying the mathematical model of multi-agent system formation reorganization path planning problem,combining 2-Opt optimization algorithm and ant colony algorithm,a ant colony algorithm based on 2-Opt optimization is designed.The solution obtained during the iterative process is optimized by 2-Opt,thereby expanding the search range of the algorithm.Simulation results show that the algorithm can effectively reduce the overall moving distance of the multi-agent system and optimize the energy consumption of the system compared with the multi-agent system formation and reconfiguration path planning using the virtual structure method.