Behavior Tree-Based Task Planning for Multiple Mobile Robots using a Data Distribution Service
This work addresses task planning for multiple mobile robots, but it is incremental as it builds on existing behavior tree methods with specific adaptations for multi-robot systems.
The authors tackled the problem of coordinating multiple mobile robots by proposing a behavior tree-based task planning framework that uses a data distribution service for asynchronous communication, and demonstrated its feasibility by successfully coordinating three robots to travel alternately to four goal positions.
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.