Decentralized multi-vehicle path coordination under communication constraints
Decentralized multi-vehicle path coordination under communication constraints
复制标题
通信约束下的分散式多车辆路径协调
DOI：
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发表时间：
2011
期刊：
影响因子：
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通讯作者：
M. Kam
中科院分区：
文献类型：
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作者：
Pramod Abichandani;Hande Y. Benson;M. Kam
提出了一种基于数学规划的分布式框架，用于生成一组受通信连通性约束的路径受限移动车辆机器人的时间最优速度分布。每个车辆机器人从固定的起点出发，沿着固定的路径向目标点移动，以避免与其他机器人相撞，并与其他机器人保持通信连接。本文的主要贡献是建立了具有运动学、动力学、防撞和通信连通性约束的多车辆路径协调问题的离散时间分散滚动区间混合整数非线性规划(RH-MINLP)模型，并应用了最新的MINLP求解技术。我们测试涉及多达十(10)个机器人的场景，以演示(I)通信连接要求对机器人速度分布的影响；以及(Ii)解计算时间对通信连接要求的依赖。
We present a mathematical programming based decentralized framework to generate time optimal velocity profiles for a group of path constrained mobile vehicle robots subject to communication connectivity constraints. Each vehicle robot starts from a fixed start point and moves towards a goal point along a fixed path so as to avoid collisions with other robots, and remain in communication connectivity with other robots. The main contribution of this paper is the discrete time decentralized Receding Horizon Mixed Integer Nonlinear Programming (RH-MINLP) formulation of the multi-vehicle path coordination problem with constraints on kinematics, dynamics, collision avoidance, and communication connectivity, and the application of state-of-the-art MINLP solution techniques. We test scenarios involving up to ten (10) robots to demonstrate (i) the effect of communication connectivity requirements on robot velocity profiles; and (ii) the dependence of the solution computation time on communication connectivity requirements.