论文标题
比例控制多机器人分配的随机调节
Proportional Control for Stochastic Regulation on Allocation of Multi-Robots
论文作者
论文摘要
由于机器人级的不确定性和对机器人行为的环境影响，用于在一组顺序任务上分发机器人集合的任何策略都遭受不准确性。我们通过建模和控制整体合奏行为来解决任务分配期间不准确的问题。我们的模型代表分配问题作为随机跳跃过程，我们调节了这种过程的均值和差异。本文的主要贡献是：建立等效随机跳跃过程的过渡速率的结构，并正式表明该方法导致脱钩参数，使我们能够调整整体分布对任务的一阶和二阶时刻，这使得在所需最终分布中降低差异的灵活性。这使我们能够直接塑造不确定性对任务分配的影响。我们介绍了一个详细的过程，以设计收益以达到所需的平均值，并显示其他参数如何影响协方差矩阵，该协方差矩阵与任务分配精度直接相关。我们的仿真和实验结果说明了任务分配过程中几个机器人合奏的成功控制。
Any strategy used to distribute a robot ensemble over a set of sequential tasks is subject to inaccuracy due to robot-level uncertainties and environmental influences on the robots' behavior. We approach the problem of inaccuracy during task allocation by modeling and controlling the overall ensemble behavior. Our model represents the allocation problem as a stochastic jump process and we regulate the mean and variance of such a process. The main contributions of this paper are: Establishing a structure for the transition rates of the equivalent stochastic jump process and formally showing that this approach leads to decoupled parameters that allow us to adjust the first- and second-order moments of the ensemble distribution over tasks, which gives the flexibility to decrease the variance in the desired final distribution. This allows us to directly shape the impact of uncertainties on the group allocation over tasks. We introduce a detailed procedure to design the gains to achieve the desired mean and show how the additional parameters impact the covariance matrix, which is directly associated with the degree of task allocation precision. Our simulation and experimental results illustrate the successful control of several robot ensembles during task allocation.
