Chaos Ant Colony Algorithm Based on Tabu Search for Data Association of SLAM

To solve the data association problem of simultaneous localization and mapping (SLAM), a chaos ant colony algorithm based on tabu search is proposed in this work. Firstly, the initial solution was built and optimized by use of the characters of positive feedback and parallel search of ant colony algorithm, and chaos disturbance was added to pheromone update to dap out local optimal. Then the search space was expanded to obtain global optimal by the character of tabu search. Finally the proposed algorithm was tested in UAV SLAM environment. The results demonstrate that the proposed algorithm could boost the rate of data association greatly. And it is effective and feasible.