论文标题
通过优先轨迹优化，多个非全面移动机器人的高效轨迹计划
Efficient Trajectory Planning for Multiple Non-holonomic Mobile Robots via Prioritized Trajectory Optimization
论文作者
论文摘要
在本文中，我们提出了一种新颖的方法，可以在障碍富的环境中有效地为多个非独立移动机器人生成无冲突的最佳轨迹。我们的方法首先采用基于图的多代理路径计划器来找到初始离散解决方案，然后使用非线性优化将此解决方案完善为平滑轨迹。我们将机器人团队分为小组，并提出了一种优先的轨迹优化方法，以提高算法的可扩展性。由于具有分离的优化框架，在某些情况下可能会出现不可行的子问题。为了解决这个问题，开发了一种新颖的分组和优先级分配策略，以增加寻找可行轨迹的可能性。与耦合的轨迹优化相比，提出的方法大大减少了计算时间，对计划的最优性有很小的影响。模拟和硬件实验验证了所提出方法的有效性和优势。
In this paper, we present a novel approach to efficiently generate collision-free optimal trajectories for multiple non-holonomic mobile robots in obstacle-rich environments. Our approach first employs a graph-based multi-agent path planner to find an initial discrete solution, and then refines this solution into smooth trajectories using nonlinear optimization. We divide the robot team into small groups and propose a prioritized trajectory optimization method to improve the scalability of the algorithm. Infeasible sub-problems may arise in some scenarios because of the decoupled optimization framework. To handle this problem, a novel grouping and priority assignment strategy is developed to increase the probability of finding feasible trajectories. Compared to the coupled trajectory optimization, the proposed approach reduces the computation time considerably with a small impact on the optimality of the plans. Simulations and hardware experiments verified the effectiveness and superiority of the proposed approach.
