Mobile Robot Path Planning Based On Improved Artificial Bee Colony Algorithm

Artificial bee colony algorithm(ABC)is one of well-known evolutionary algorithms and has been successfully applied to many continuous or combinatorial optimization problems.In order to further improve the performance of the algorithm,an improved ABC algorithm(IABC)is proposed in this paper,which improves the main stages of the algorithm.First,we establish a chaotic mapping rule by introducing a chaos operator in the initial position generation rules to ensure the ergodicity of the initial position.Then,an equidistant distributed parallel search rule is designed,on the basis of which,neighborhood search of the initial position is conducted to improve the convergence speed and the local search ability.Next,using the parallel selection strategy of roulette and anti-roulette,the anti-roulette mechanism is introduced to select the current poor position to jump out of the local optimum.At the same time,a global updating mechanism based on the gravitational potential field is proposed to guide the abandonment and supplement of the position and speed up the convergence of the algorithm.The results show that the IABC algorithm can improve the convergence speed and the quality of solution without premature convergence into local optimum.After the algorithm is improved,introduce Taguchi analysis to further analyze the structure of IABC,which focuses on the factor level setting related to the following key factors: chaotic mapping rules in the initial position generation rules,equidistant distributed parallel search rules,parallel selection strategies and update threshold in the global update mechanism.The results display that the optimal combination of factor levels has been achieved in the IABC.Finally,the IABC algorithm is applied to path planning of mobile robots.Taguchi orthogonal experiment is used to analyze the algorithm parameters and the objective function,and the experimental parameter values are selected to carry out path planning comparison experiment based on ABC algorithm and IABC algorithm.The experimental results show that the IABC algorithm has a better path quality and improves the planning efficiency of mobile robot path.