Three-dimensional Virtual Multitask Planning Based on the Improved Ant Colony Optimization Algorithm

Abstract

Background: The most application scenario modeling of the obstacle avoidance in the path planning algorithm is based on the simplified two-dimensional grid model, so most algorithms are not suitable for the 3D space. In the real three-dimensional (3D) space path planning problem is more complicated. Firstly, the 3D map data are too big leading to complex computation. Secondly, the serial searching mode of traditional search algorithm leads low efficiency in dealing with the multitasking collaborative planning problem. Thirdly, the algorithm is easy to premature and falls into local optimal solution in dealing with a three-dimensional multitasking problem. And the proposed algorithm in this paper can well solve these problems. Materials and Methods: The real three-dimensional space model is created by the Vega Prime® in this study, overcoming the limitations of the two-dimensional model. In order to reduce the amount of operation data of the 3D environment, the map range is reduced and the path is enlarged by the points which are evenly interpolated in the path. Then change the traditional serial processing mode of the algorithm and the ant colony is divided to some subgroups and the optimal solution in each subgroup can be solved when the constraints are satisfied, then the multi-task path planning is achieved. Finally aiming at the condition of the algorithm is easy to premature, the neighborhood precise search strategy is adopted to improve the transition probabilities and walking strategies of the ant colony optimization algorithm and then the local search ability of the algorithm is improved. Results: As the simulation results shown, the search capability of the improved ant colony intelligence algorithm is enhanced, thus the success probability of path-finding is increased. Meanwhile, the convergence speed of the algorithm is improved, leading reduced time of path-planning. Furtherly, the algorithm is proved more efficient and feasible by comparative experiment with PSO, GA and APF algorithm. Conclusion: So, the multitasking path planning problem in three-dimensional virtual scenes is solved effectively. And with the multichannel-joint 3D simulation system, the effectiveness of the algorithms for three-dimensional space can be tested by the simulation without hardware conditions and reduce the cost and the risk of late hardware using.