Decentralized Motion Planning for Multiagent Collaboration Under Coupled LTL Task Specifications
提出一种分散协作方案，通过解耦乘积自动机并利用tableau和gossip协议实现实时消息交换，解决多智能体系统在耦合线性时序逻辑任务下的运动规划问题，并增强对节点故障的鲁棒性。
This article proposes a decentralized collaboration scheme for the motion planning of multiagent systems under coupled linear temporal logic task specifications. In order to alleviate the massive computational complexity in centralized methods, coupled edges are introduced to decouple the product automata, and then the path of each agent is synthesized according to local messages. Furthermore, in order to achieve the real-time message exchange, the tableau and gossip protocol are employed during online communication, resulting in a distributed collaboration scheme. Finally, based on the resultant decoupled product automata, a united agent model is designed to deal with partial node failures, yielding a more robust collaboration scheme. Simulations are conducted to demonstrate the effectiveness and superiority of the proposed methods.