This paper presents a simultaneous task assignment and trajectory planning method for unmanned system swarm by using optimal transport and model predictive control (OT-MPC). Unlike the conventional hierarchical assignment and planning, the proposed approach addresses both the task assignment and trajectory planning subproblems concurrently. To be specific, a unified cost function is designed to solve task assignment and trajectory planning problem. Moreover, the multi-tasks are assigned by using optimal transport, which establishes an optimal mapping between tasks and unmanned system vehicles based on transportation cost. The trajectory planning is achieved by using model predictive control, which generates high-quality navigation trajectories considering obstacle avoidance. Finally, the proposed method is applied to the unmanned surface vehicles swarm. Numerical simulations and experiments were conducted to validate the effectiveness of the proposed method.

本文提出了一种利用最优传输和模型预测控制（OT-MPC）的无人系统群同时任务分配和轨迹规划方法。与传统的分层分配和规划不同，所提出的方法同时解决任务分配和轨迹规划子问题。具体来说，设计统一的成本函数来解决任务分配和轨迹规划问题。此外，多任务通过最优运输进行分配，根据运输成本建立任务和无人系统车辆之间的最优映射。轨迹规划通过模型预测控制实现，生成考虑避障的高质量导航轨迹。最后，将所提出的方法应用于无人水面车辆群。进行了数值模拟和实验来验证所提方法的有效性。