论文标题
异构多机构团队的最佳组成，以覆盖绩效保证的覆盖范围问题
Optimal Composition of Heterogeneous Multi-Agent Teams for Coverage Problems with Performance Bound Guarantees
论文作者
论文摘要
我们考虑确定异质多代理团队最佳组成的问题，包括与不同的代理相关的成本并受到最大允许数量的代理数量的上限。我们在不引入原始问题的情况下提出资源分配问题。我们开发了分布式的投影梯度上升（PGA）算法来解决最佳团队组成问题。为了处理非跨性别性，我们使用贪婪的方法初始化算法，并利用覆盖物目标函数的间相和曲率特性，从而在优化问题解决方案中得出新颖的紧密性能保证。包括数值示例，以验证这种方法在不同的任务空间配置和不同异质的多代理集合中的有效性。使用商业混合成员非线性编程问题求解器获得的比较结果证明了分布式PGA算法的准确性和计算效率。
We consider the problem of determining the optimal composition of a heterogeneous multi-agent team for coverage problems by including costs associated with different agents and subject to an upper bound on the maximal allowable number of agents. We formulate a resource allocation problem without introducing additional non-convexities to the original problem. We develop a distributed Projected Gradient Ascent (PGA) algorithm to solve the optimal team composition problem. To deal with non-convexity, we initialize the algorithm using a greedy method and exploit the submodularity and curvature properties of the coverage objective function to derive novel tighter performance bound guarantees on the optimization problem solution. Numerical examples are included to validate the effectiveness of this approach in diverse mission space configurations and different heterogeneous multi-agent collections. Comparative results obtained using a commercial mixed-integer nonlinear programming problem solver demonstrate both the accuracy and computational efficiency of the distributed PGA algorithm.
