FSOC: Flexible Subgrouping and Ordering of Multirobot Coordination for Convoying Multiple Scattered Targets

IF 5 3区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS IEEE Transactions on Control of Network Systems Pub Date : 2024-04-25 DOI:10.1109/TCNS.2024.3393643
Bin-Bin Hu;Weijia Yao;Henglai Wei;Chen Lv
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Abstract

In this article, we propose the flexible subgrouping and ordering coordination (FSOC) algorithm that enables a team of robots to cooperatively convoy multiple scattered targets (MSTs) of different moving velocities, where each target is convoyed into the interior of distinct convex hulls formed by different subgroups of robots in dynamic environments. Therein, the algorithm/convoying is flexible in the sense that no specific numbers and indexes of robots are preassigned for each subgroup, and no specific spatial ordering sequences of robots are predetermined for each convex hull. To attain such a flexible convoying for scattered targets, we first encode the three subtasks of flexible subgrouping, target convergence, and neighboring collision avoidance into control barrier function constraints and then formulate the FSOC problem as a decentralized constraint-based task-execution optimization one. In particular, by embedding convoying matching conditions into hard integer constraints and soft cost functions, the robots can be divided into subgroups of flexible numbers and indexes. Then, for each subgroup of robots, the flexible-ordering convex hull for each specific target is realized through the balance between the attraction resulting from the target convergence constraints and the repulsion from time-varying collision avoidance constraints. Rigorous analysis is provided to guarantee the asymptotic convergence of the closed-loop systems, which have strong nonlinear couplings due to the flexible subgrouping and ordering. Finally, extensive 2-D and 3-D simulations have been conducted to confirm the effectiveness of the proposed algorithm across different initial positions, the robustness in the face of robot sudden breakdown and target sudden appearances, the adaptability to navigate through obstacle environments, and the scalability when accomplishing high-dimensional MST convoying missions.
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FSOC:灵活分组和排序多机器人协调,护送多个分散目标
在本文中,我们提出了一种柔性子分组和排序协调(FSOC)算法,该算法使机器人团队能够在动态环境中协作护送不同移动速度的多个分散目标(mst),其中每个目标被护送到由不同机器人子组组成的不同凸包的内部。其中,算法/护航的灵活性在于不为每个子群预先分配机器人的特定数量和指标,不为每个凸包预先确定机器人的特定空间排序顺序。为了实现对分散目标的柔性护航,首先将柔性子分组、目标收敛和相邻避碰三个子任务编码为控制障碍函数约束,然后将FSOC问题表述为基于分散约束的任务执行优化问题。特别是,通过将运输匹配条件嵌入到硬整数约束和软成本函数中,可以将机器人划分为柔性数字和索引的子群。然后,通过平衡目标收敛约束所产生的吸引力和时变避碰约束所产生的斥力,对每个机器人子群实现针对每个特定目标的柔性排序凸壳。对由于柔性子群和排序而具有强非线性耦合的闭环系统进行了严密的分析,保证了系统的渐近收敛性。最后,进行了大量的二维和三维仿真,验证了该算法在不同初始位置的有效性、面对机器人突然故障和目标突然出现的鲁棒性、在障碍物环境中导航的适应性以及在完成高维MST护送任务时的可扩展性。
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来源期刊
IEEE Transactions on Control of Network Systems
IEEE Transactions on Control of Network Systems Mathematics-Control and Optimization
CiteScore
7.80
自引率
7.10%
发文量
169
期刊介绍: The IEEE Transactions on Control of Network Systems is committed to the timely publication of high-impact papers at the intersection of control systems and network science. In particular, the journal addresses research on the analysis, design and implementation of networked control systems, as well as control over networks. Relevant work includes the full spectrum from basic research on control systems to the design of engineering solutions for automatic control of, and over, networks. The topics covered by this journal include: Coordinated control and estimation over networks, Control and computation over sensor networks, Control under communication constraints, Control and performance analysis issues that arise in the dynamics of networks used in application areas such as communications, computers, transportation, manufacturing, Web ranking and aggregation, social networks, biology, power systems, economics, Synchronization of activities across a controlled network, Stability analysis of controlled networks, Analysis of networks as hybrid dynamical systems.
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