| Mobile robot path planning is the core part in robot navigation technology, and it is benefical to adapt to the complex environment, flexible and effective mobile robot path planning under uncertain environment is the important prerequisite to complete the various tasks smoothly and successfully. Path planning problem can be transformed into a function optimization problem with constraints, it is mainly related to environmental information modeling, search the optimal or sub-optimal collision-free path based on a model of the environment and handle uncertainty in environmental models.Particle Swarm Optimization(PSO) algorithm is a swarm intelligence of heuristic search algorithm, in recent years, it has become the most rapidly developing intelligent search algorithm, and widely used in the field of system identification, signal processing, power systems, function optimization, factory scheduling,ect. Since PSO algorithm shows a superior performance in solving complex problems, many researchers apply it to mobile robot path planning problem and achieved good optimization results.This paper introduces the domestic and foreign research status of mobile robot path planning algorithm, analyses the advantages and disadvantages of each algorithm and application prospects, on this basis, according to the characteristics of robot path planning, the link graph method is adopted for the environment modeling, taking into account the environment obstacles while introducing hazard information into the environment model, we propose two mobile robot path planning based on particle swarm algorithm, which based on PSO and genetic hybrid algorithm and the age and challenger operators PSO path planning method. The main research content is as follows:First of all, the research status of mobile robotics research were analyzed, and lay a theoretical foundation for subsequent robot path planning research.Secondly, the PSO algorithm described in detail, analyzed the structure and topology of various parameters on particle swarm algorithm describes various improved particle swarm algorithm, and the effect of particle swarm optimization algorithms were tested to verify.Then, according to the characteristics of mobile robot path planning, the use of the link graph method to establish environmental model, a path planning algorithm based on PSO and genetic algorithm mixed, the concrete implementation steps of the algorithm, discussed and analyzed the effect parameter settings for planning the impact of the final results are given path planning algorithm, the results show that the method has good performance avoidance.In some robot path planning special occasions, in addition to considering obstacle avoidance factors, the need to consider the environment hazards, robot path planning for this problem, particle swarm path planning method based on the age of the Challenger Operators the simulation results show that this method can quickly plan a collision path in the presence of environmental hazards, and avoid plunging local optimum.Finally, this paper summarizes the work, while the development of mobile robot path planning in the future. |
