In this study, we propose task planning framework for multiple robots that builds on a behavior tree (BT). BTs communicate with a data distribution service (DDS) to send and receive data. Since the standard BT derived from one root node with a single tick is unsuitable for multiple robots, a novel type of BT action and improved nodes are proposed to control multiple robots through a DDS asynchronously. To plan tasks for robots efficiently, a single task planning unit is implemented with the proposed task types. The task planning unit assigns tasks to each robot simultaneously through a single coalesced BT. If any robot falls into a fault while performing its assigned task, another BT embedded in the robot is executed; the robot enters the recovery mode in order to overcome the fault. To perform this function, the action in the BT corresponding to the task is defined as a variable, which is shared with the DDS so that any action can be exchanged between the task planning unit and robots. To show the feasibility of our framework in a real-world application, three mobile robots were experimentally coordinated for them to travel alternately to four goal positions by the proposed single task planning unit via a DDS.
翻译:在此研究中,我们建议了基于行为树(BT)的多个机器人的任务规划框架。 BT与数据分发服务(DDS)进行通信,以发送和接收数据。由于一个根节点产生的一个单项根节点的标准BT不适用于多个机器人,因此建议了一种新型的BT动作和改进节点,以便通过一个DDS同步地控制多个机器人。为高效规划机器人的任务,将使用拟议任务类型执行一个单一的任务规划单位。任务规划单位通过一个单一的联结式BT向每个机器人同时分配任务。如果任何机器人在执行指定任务时出现故障,将执行另一个嵌入机器人内部的BT;机器人进入回收模式以克服错误。要履行这一功能,BT与任务相对应的行动将被定义为变量,与DDS共享,以便任务规划单位和机器人之间能够交换任何行动。为了在现实世界应用程序中显示我们框架的可行性,3个移动机器人在进行实验协调,以便他们通过提议的单项任务规划,通过一个单项任务计划,通过一个单项任务将一个任务转到4个目标位置。