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中文摘要：
提出了一种求解群集机器人协作任务规划问题的均分点蚁群算法（EDPACA）。通过多组蚂蚁群相互协作搜索，构架了一种新蚁群算法的解结构，并设计了更合理的评估函数，使其在评价时充分考虑均衡任务点探测，最后利用2-opt技术解决了各子周游路径的交叉问题，获得了总代价最优的解。该算法将蚁群技术首次应用于集群机器人的任务调度规划中，成功解决了中大规模任务规划问题。仿真实验结果表明，均分点蚁群算法能提高群集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：
An equal division point ant colony algorithm （EDPACA） was proposed to solve the swarm-robot mission planning problem. Firstly, the algorithm was designed by a novel solution construction through muhi-group ants＇ cooperative search, and a more reasonable evaluation function which sufficiently considered the equal division mission point factor. Secondly, the crossover problems of sub-circular paths were solved by the 2-opt method. It is the first time to apply an ant colony algorithm to swarm-robot mission planning, the proposed algorithm can solve large scale mission planning problems effectively. The experiment results show that EDPACA improved the efficiency of executing a large number of tasks. Additionally, it also provides a new idea to solve the multi-person traveling salesman problem.
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