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中文摘要：
针对群机器人协作任务规划问题，提出一种正交混沌蚁群算法（OCACA）对其进行求解．该算法的思想是首先采用正交法对任务目标进行聚类，然后利用混沌技术对蚁群初始解进行优化，改进初始个体质量，并用混沌扰动策略避免搜索进入局部最优，最终获得了总代价最优解．该算法将正交混沌蚁群算法首次应用于群机器人的任务规划中。成功解决了中大规模任务规划问题．仿真实验结果表明：正交混沌蚁群算法能提高多机器人执行任务的效率，同时也是解决多旅行商问题的另种新思路．
英文摘要：
Aiming at swarm-robots system＇s cooperative mission planning problem, an Orthogonal-cluster Chaos Ant Colony Algorithm （OCACA） is presented. The idea of the algorithm is that first use orthogonal method to cluster the target points, then adopt chaos technology to optimize initial solution of the ant colony to improve individual quality and chaos perturbation is utilized to avoid the search being trapped in local optimum. It＇s the first time to apply OCACA in swarm-robot mission planning, and the algorithm solve large-scale mission planning problem successfully. Simulation result show that the algorithm works well in improving the efficiency of executing tasks of swarm-robots. Additionally, it＇s a novel ideal to solve multiple traveling salesmen problem.
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