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中文摘要：
在动态环境分配很多项探索任务到活动机器人的一个队的问题被学习。队使命是访问几个分布式的目标。目标的路径费用与一个机器人不得不移动访问目标的距离成正比。队目的是在所有目标上最小化目标的平均路径费用。发现最佳的分配是强烈 NP 难的。建议算法能生产一个在最佳附近的答案到它。分配能以机器人为目标由投标的多周围单个条款的拍卖被扔。在每个拍卖回合，一个目标被分到生产目标的最低路径费用的一个机器人。分配目标形成每棵树通信的一个森林一个机器人探索目标集合。每个机器人在它的目标树上通过深度优先的搜索构造一条探索路径。建议算法的时间复杂性是多项式。模拟实验证明分配方法是有效的。
英文摘要：
The problem of allocating a number of exploration tasks to a team of mobile robots in dynamic environments was studied. The team mission is to visit several distributed targets. The path cost of target is proportional to the distance that a robot has to move to visit the target. The team objective is to minimize the average path cost of target over all targets. Finding an optimal allocation is strongly NP-hard. The proposed algorithm can produce a near-optimal solution to it. The allocation can be cast in terms of a multi-round single-item auction by which robots bid on targets. In each auction round, one target is assigned to a robot that produces the lowest path cost of the target. The allocated targets form a forest where each tree corresponds a robot＇s exploring targets set. Each robot constructs an exploring path through depth-first search in its target tree. The time complexity of the proposed algorithm is polynomial. Simulation experiments show that the allocating method is valid.
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