This work presents a distributed MPC-based approach to solving the problem of multi-agent point-to-point transition with optimization-based collision avoidance. The problem is formulated, motivated by the work on collision avoidance for multi-agent systems and dynamic obstacles. With modifications to the formulation, the problem is converted into a distributed problem with a separable objective and coupled constraints. The problem is divided into local sub-problems and solved using Alternating Directions Method of Multipliers(ADMM) applied on an augmented local lagrangian objective.This work aims to understand the multi-agent point-to-point transition problem as an extension of optimization-based collision avoidance and analyze the aspects of computational times, reliability, and optimality of the solution obtained.

中文翻译：

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多智能体动力系统目标达成任务中基于优化的碰撞避免

这项工作提出了一种基于分布式 MPC 的方法，通过基于优化的碰撞避免来解决多代理点对点转换问题。该问题是由多智能体系统和动态障碍物的碰撞避免工作所激发的。通过对公式的修改，问题被转换为具有可分离目标和耦合约束的分布式问题。该问题分为局部子问题，并使用应用于增强局部拉格朗日目标的交替方向乘子法（ADMM）解决。这项工作旨在将多智能体点对点转换问题理解为优化的扩展-基于碰撞避免并分析计算时间、可靠性和所获得解决方案的最优性等方面。