无碰撞源寻找与群体控制的多智能体系统
Collision-free Source Seeking and Flocking Control of Multi-agents with Connectivity Preservation
AI总结：
本文提出了一种基于分布式控制的多智能体系统源寻找与群体控制方法，通过优化问题解决碰撞避免和连通性保持问题。
摘要：
本文提出了一种分布式源寻找和群体控制方法，用于具有非完整约束的网络化多智能体系统。基于相同的 onboard 传感器系统，该系统测量局部源场。通过指定一个领导者智能体寻找源，其余跟随者智能体在保持连通性的无向网络中，通过分布式群体控制律安全地与邻居形成凝聚力群体。为保证所有智能体的安全分离和群体运动，并解决与 Reynolds
英文摘要：
In this article, we present a distributed source-seeking and flocking control method for networked multi-agent systems with non-holonomic constraints. Based solely on identical on-board sensor systems, which measure the source local field, the group objective is attained by appointing a leader agent to seek the source while the remaining follower agents safely form a cohesive flocking with their neighbors using a distributed flocking control law in a connectivity-preserved undirected network. To guarantee safe separation and group motion for all agents and to solve the conflicts with the "cohesion" flocking rule of Reynolds, the distributed control algorithm is solved individually through feasible CBF-based optimization problem with complex constraints, which guarantees the inter-agent collision avoidance and connectivity preservation. Stability analysis of the closed-loop system is presented and the efficacy of the methods is shown in simulation results.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
