Based On Ant Colony Algorithm For Robot Path Planning And Improvement

Regarding its application in robotic path planning, ant colony algorithm is discussed in this paper. After analyizing and summarizing typical application schemes now in existence, several improved algorithms were proposed whose effectiveness and advantages were then proved by multitudes of simulation experiments.The substance in this paper are as follows:1. Introduction of robotic path planningHistory and present researth into path planning algorithms for mobile robots were expatianted as well as categorized. Basic thought of Evolutionary Computation and Swarm Intelligence were introduced as the representation algolithm of computational intelligence, and also their implementation.2. Introduction of ant Colony AlgorithmIntroducing the basic thought and the application area of ant Colony Algorithm from the history of it.The TSP (Traveling Salesman Problem) was discussed in this section and a detailed illustration and Algorithm flow were gived .Development and current research status of ACO's implementation designs for robotic path planning was summarized3. ACO with "alarm element policy algorithm" (ACO- Ant Colony Optimization)The "alarm element policy algorithm" was gived according to analyze the pathplanning policy of so called "turn around structure map". The pheromone refresh algorithm was improved in this new algorithm and also added "backward distance illumination policy" ( BDLP ) combining with the"BDLP-NAF"(nod access frequency) function in the algorithm to improve the randomicity problem of switching motion direction. These improvement expanded the suitability of ACO algorithm path planning on more complex maps.4. ACO with "Honey Candy Broadcast algorithm" and "Less-1 policy algorithm"Thinking about the improvement of the process of path planning problem, theACO with "Honey Candy Broadcast algorithm" and "Less-1 policy algorithm" was gived. The detail introduction of "Honey Candy Broadcast algorithm" and "Less-1 policy algorithm " was also gived.This algorithm makes more enhancive of an ACO algorithm using in the path planning problem.