论文标题
使用强大的MPC和混合智能编程在连接性约束下，针对一组差速器机器人的实时运动计划和决策制定
Real-time motion planning and decision-making for a group of differential drive robots under connectivity constraints using robust MPC and mixed-integer programming
论文作者
论文摘要
这项工作涉及计划轨迹和分配由差速器机器人组成的多代理系统（MAS）的任务的问题。我们提出了一种多等级层次控制结构，该结构采用了基于强大模型预测控制（MPC）的规划仪，并使用混合智能编程（MIP）编码。规划师计算轨迹并为组的每个元素进行实时分配任务，同时也保证MAS的通信网络始终可以牢固地连接。此外，我们提供了一种基于数据的方法来估算强大的MPC公式所需的干扰集。在两个充满障碍的场景中的实验证明了结果
This work is concerned with the problem of planning trajectories and assigning tasks for a Multi-Agent System (MAS) comprised of differential drive robots. We propose a multirate hierarchical control structure that employs a planner based on robust Model Predictive Control (MPC) with mixed-integer programming (MIP) encoding. The planner computes trajectories and assigns tasks for each element of the group in real-time, while also guaranteeing the communication network of the MAS to be robustly connected at all times. Additionally, we provide a data-based methodology to estimate the disturbances sets required by the robust MPC formulation. The results are demonstrated with experiments in two obstacle-filled scenarios
